Methods and systems for digitally counting features on arrays

ABSTRACT

Methods, systems and platforms for digital imaging of multiple regions of an array, and detection and counting of the labeled features thereon, are described.

CROSS-REFERENCE

This application claims the benefit of U.S. Provisional Application No.61/887,853, filed Oct. 7, 2013, which application is incorporated hereinby reference.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has beensubmitted electronically in ASCII format and is hereby incorporated byreference in its entirety. Said ASCII copy, created on Nov. 5, 2014, isnamed 41977-711.201_SL.txt and is 255,804 bytes in size.

BACKGROUND OF THE INVENTION

Array technologies have been widely used in biomedical studies for thedetection of biomolecules and profiling of gene expression levels, etc.Arrays are typically comprised of immobilized probes which can bind toor hybridize with target molecules in a sample. Detection of binding orhybridization events is often achieved through the use of optical labels(e.g. fluorophores) and scanning or imaging techniques (e.g.fluorescence scanning or imaging). A feature on an array is a smallregion of immobilized probes that are specific for a given targetmolecule, e.g. probes that hybridize to specific DNA or RNA sequences.Identifying the pattern of labeled features on a hybridized array thusprovides information about specific molecules, e.g. DNA or RNA moleculesin the sample, which in turn can provide valuable data in biomedicalstudies. Two important engineering requirements for providing highquality, quantitative data for biomedical investigations are (i) tocorrectly image the hybridized arrays, and (ii) to correctly analyze theimages to extract quantitative data. Existing optical imaging systemstypically image one region of an array at a time, which can be a slowprocess if a number of different regions need to be imaged. In addition,current methods of image analysis typically determine a signal intensitylevel (i.e. an analog quantity) for each array feature. Intensity levelmeasurements are often subject to a variety of instrumental drift andanalysis errors, therefore improved methods for determining whether ornot target molecules are bound to a given array feature, and improvedmethods for transforming that data into quantitative measures of thenumber of target molecules present in a sample, are of great importanceto expanding the use of array technologies in biomedical applications.

SUMMARY OF THE INVENTION

The methods, systems, and platforms of the present disclosure providemeans for digital counting of labeled features on arrays, and therebyenable quantitative determination of the number of target moleculespresent in a sample through the use of stochastic labeling techniques.

In some embodiments, an array reader system comprising an output unitfor calculating an absolute number of target molecules in a sample isdescribed, wherein the array reader system is configured to read anarray comprising a plurality of labeled and non-labeled features. Insome embodiments, the array reader system may further comprise anoptical imaging system. In some embodiments, the calculation of absolutenumber of target molecules in a sample is based on transforming opticalimage data produced by the optical imaging system into a count of thenumber of labeled and non-labeled features on an array. In someembodiments, the output unit comprises a digital processor andexecutable software, wherein the executable software comprises computercode for transforming optical image data into a count of the number oflabeled and non-labeled features. In some embodiments, the arraycomprises a microarray, microscope slide, or microwell plate.

In some embodiments of the disclosed array reader system, the opticalimaging system has a magnification of less than 1, equal to 1, orgreater than 1. In some embodiments, the optical imaging systemcomprises a fluorescence imaging system. In some embodiments, theoptical imaging system comprises a phosphorescence imaging system. Insome embodiments, the optical imaging system comprises an imaging systemthat operates in a transmitted light, reflected light, or scatteredlight imaging mode, or combinations thereof. In some embodiments, theoptical imaging system comprises one or more image sensors, wherein theone or more image sensors have a resolution of at least 320×240 pixels.In some embodiments, the one or more image sensors are CCD imagesensors, while in some embodiments, the one or more image sensors areCMOS image sensors. In some embodiments, the one or more image sensorscomprise one or more circuit boards. In some embodiments, the opticalimaging system further comprises one or more components selected fromthe group including, but not limited to, a microscope objective, acamera lens, a finite-conjugate lens, an infinite-conjugate lens, aplano-convex lens, a double convex lens, a plano-concave lens, a doubleconcave lens, an achromatic cemented doublet, or a bandpass filter. Insome embodiments, the optical imaging system comprises a fluorescenceimaging system that is designed for use with fluorescein, Cy3, Cy5, orphycoerythrin fluorophores. In some embodiments, the optical imagingsystem further comprises an illumination system including at least onelight source, wherein the at least one light source is an LED or LEDassembly. In some embodiments, the at least one light source iselectronically synchronized with the image sensor, the at least onelight source being turned on when the image sensor is acquiring an imageand turned off when the image sensor is not acquiring an image.

In some embodiments of the disclosed array reader system, theillumination system is an off-axis illumination system that satisfiesthe Scheimpflug condition. In some embodiments, the illumination systemis an off-axis illumination system does not satisfy the Scheimpflugcondition. In some embodiments, the illumination system is an off-axisillumination subsystem comprising a Kohler illumination system. In someembodiments, the illumination system is an off-axis illumination systemcomprising an Abbe illumination system. In some embodiments, theillumination system is an epi-illumination system comprising a Kohlerillumination system. In some embodiments, the illumination system is anepi-illumination system comprising an Abbe illumination system. In someembodiments, the illumination system is a trans-illumination systemcomprising a Kohler illumination system. In some embodiments, theillumination system is a trans-illumination system comprising an Abbeillumination system.

In some embodiments of the disclosed array reader system, the opticalimaging system further comprises a translation stage, wherein thetranslation stage is a single-axis translation stage, a dual-axistranslation stage, or a multi-axis translation stage.

In some embodiments of the disclosed array reader system, the opticalimaging system and output unit are combined within a single, stand-aloneinstrument. In some embodiments, the optical imaging system and outputunit are configured as separate instrument modules.

In some embodiments of the disclosed array reader system, the executablesoftware automatically locates features of the array within the acquiredimage. In some embodiments, the executable software also performs localbackground correction by (i) centering a predefined analysis window oneach array feature within an image, (ii) calculating an intensity valuestatistic for signal and background pixels according to a predefinedpattern of pixels within the feature, and (iii) utilizing the signal andbackground intensity value statistics to calculate a backgroundcorrected signal intensity value for each feature.

In some embodiments of the disclosed array reader system, the executablesoftware performs a k-means clustering analysis of the backgroundcorrected signal intensity values for the complete set of arrayfeatures, thereby determining a dynamic signal intensity threshold fordiscrimination between labeled and non-labeled features of the array. Insome embodiments, the executable software also performs a k-medoidsclustering analysis of the background corrected signal intensity valuesfor the complete set of array features, thereby determining a dynamicsignal intensity threshold for discrimination between labeled andnon-labeled features of the array. In some embodiments, the executablesoftware also performs a mixture model statistical analysis of thebackground corrected signal intensity values for the complete set ofarray features, thereby determining a dynamic signal intensity thresholdfor discrimination between labeled and non-labeled features of thearray. In some embodiments, the executable software also performs anempirical analysis based on sorting of background corrected signalintensity values for the complete set of array features, therebydetermining a dynamic signal intensity threshold for discriminationbetween labeled and non-labeled features of the array. In someembodiments, the executable software also performs an empirical analysisbased on sorting of pairwise differences in background corrected signalintensity values for the complete set of array features, therebydetermining a dynamic signal intensity threshold for discriminationbetween labeled and non-labeled features of the array. In someembodiments, the executable software module also performs one or morestatistical analyses of the background corrected signal intensity valuesfor the complete set of array features, thereby determining a dynamicsignal intensity threshold for discrimination between labeled andnon-labeled features of the array, and wherein the one or morestatistical analyses are selected from the list including, but notlimited to, k-means clustering, k-medoids clustering, mixture modelstatistical analysis, or an empirical analysis.

In some embodiments of the disclosed array reader system, the executablesoftware calculates the absolute number of target molecules in a samplebased on the number of labeled and non-labeled features detected and thepredictions of the Poisson distribution. In some embodiments, theexecutable software also calculates a confidence interval for the numberof target molecules.

Also disclosed herein is a digital imaging platform comprising: (a) anoptical instrument configured to generate an image of one or moreregions of an array, wherein the array comprises a plurality of featurescomprising oligonucleotide probes, and wherein the oligonucleotideprobes are complementary to a set of labels; and (b) a digitalprocessor, wherein the digital processor is configured to perform imageanalysis comprising: (i) transforming background corrected signalintensities for a plurality of features to produce binary output datathat determines the number of labeled and non-labeled features in theone or more regions of the array; and (ii) calculating a number oftarget molecules present in a sample based on the number of labeled andnon-labeled features detected within the one or more regions of thearray. In some embodiments, the image analysis further comprisesautomatically locating the features of the array within the image. Insome embodiments, the image analysis further comprises correcting asignal intensity for each feature for a local background intensity. Insome embodiments, the image analysis further comprises performing one ormore statistical analyses of the corrected signal intensities for aplurality of features to define one or more dynamic signal intensitythresholds for the one or more regions of the array, where thestatistical analyses are selected from the list including, but notlimited to, k-means clustering, k-medoids clustering, mixture modelstatistical analysis, or an empirical analysis. In some embodiments, thecalculation of the number of target molecules present in a sample isbased on both the number of labeled and non-labeled features detectedwithin the one or more regions of the array and on the predictions ofthe Poisson distribution.

Disclosed herein is an imaging platform comprising: (a) an opticalinstrument configured to generate an image of one or more regions of anarray, wherein the array comprises a plurality of features, and whereinthe plurality of features comprise a set of oligonucleotide probes, andwherein the oligonucleotide probes are complementary to a set of labels;and (b) a processor configured to perform image analysis, wherein theimage analysis comprises: (i) reading the image generated by the opticalinstrument; (ii) locating the features of the array within the image;(iii) measuring a signal intensity for each feature; (iv) measuring alocal background intensity for each feature; (v) calculating a localbackground corrected signal intensity for each feature using the signalintensity and local background intensities; (vi) analyzing the localbackground corrected signal intensities for the complete set of featuresto determine a dynamic signal intensity threshold for discriminatingbetween labeled and non-labeled features; and (vii) calculating a numberof target molecules present in a sample based on the number of labeledand non-labeled features detected and the predictions of the Poissondistribution. In some embodiments, the image generated by the opticalinstrument is a fluorescence image. In some embodiments, the imagegenerated by the optical instrument is a phosphorescence image. In someembodiments, the image generated by the optical instrument is atransmitted light, reflected light, or scattered light image. In someembodiments, the image analysis further comprises reading an image thathas been previously acquired and stored in a memory device. In someembodiments, locating the features of the array within the imagecomprises identifying predefined fiducial features on the array. In someembodiments, the calculation of a local background corrected signalintensity is performed by (i) centering a predefined analysis window oneach feature within the image, (ii) calculating an intensity valuestatistic for signal and background pixels according to a predefinedpattern of pixels within the feature, and (iii) utilizing the signal andbackground intensity value statistics to calculate a local backgroundcorrected signal intensity for each feature. In some embodiments, theintensity value statistic used for calculating a local backgroundcorrected signal intensity for each feature is selected from the listincluding, but not limited to, the mean, the median, or the ratio ofsignal to background intensities. In some embodiments, the analyzing oflocal background corrected signal intensities for the complete set offeatures to determine a dynamic signal intensity threshold comprisesperforming one or more statistical analyses selected from the listincluding, but not limited to, k-means clustering, k-medoids clustering,mixture model statistical analysis, or an empirical analysis. In someembodiments, the analyzing of local background corrected signalintensities for the complete set of features to determine a dynamicsignal intensity threshold comprises fitting a model function to theintensity data by varying model parameters. In some embodiments, theanalyzing of local background corrected signal intensities for thecomplete set of features to determine a dynamic signal intensitythreshold comprises maximizing a quality metric relating to astatistical difference between intensities above the threshold and belowthe threshold.

Also disclosed herein is a non-transitory computer readable mediumstoring a program that calculates a number of labeled features on anarray, wherein the array comprises a plurality of feature sets, andwherein individual features of a feature set comprise a set ofoligonucleotide probes that are capable of hybridizing to a set oflabels, the non-transitory computer readable medium comprising: (a)computer code that locates individual features of the array within adigital image of the array; (b) computer code that performs a localbackground correction of a signal intensity for each feature; (c)computer code that analyzes the corrected signal intensity data for thecomplete set of features and determines a corrected signal intensitythreshold; and (d) computer code that transforms the corrected signalintensity for each feature into binary output data, thereby providing acount of the number of labeled features on the array. In someembodiments, the computer code for locating individual features of thearray within the digital image comprises identifying predefined fiducialfeatures on the array. In some embodiments, the computer code forperforming a local background correction of signal intensity for eachfeature comprises a calculation utilizing a statistic for signal andbackground intensities selected from the list including, but not limitedto, the mean, the median, or the ratio of signal to backgroundintensities. In some embodiments, the computer code for analyzingcorrected signal intensities for the complete set of features todetermine a corrected signal intensity threshold comprises performingone or more statistical analyses selected from the list including, butnot limited to, k-means clustering, k-medoids clustering, mixture modelstatistical analysis, or an empirical analysis.

Also disclosed herein is a computer implemented method for performinglocal background correction of array signal intensity data, the methodcomprising: (a) centering a predefined data analysis window on a featurewithin a digital image of the array; (b) calculating an intensity valuestatistic for signal and background pixels according to a predefinedpattern of pixels within or around the array feature; and (c) utilizingthe signal and background intensity value statistics to calculate abackground corrected signal intensity for the array feature. In someembodiments, the computer implemented method further comprisesautomatically locating the array feature using a predefined set offiducial features on the array. In some embodiments, the intensity valuestatistic used for calculation of a background corrected signalintensity is selected from the list including, but not limited to, themean, the median, or the ratio of signal to background intensities.

Disclosed herein is a computer implemented method for determining adynamic image intensity threshold for use in discriminating betweenlabeled and non-labeled features on an array comprising a plurality oflabeled and non-labeled features, the computer implemented methodcomprising: (a) measuring image intensity data for each feature of thearray; (b) performing a local background correction on the imageintensity data for each feature on the array; and (c) performing one ormore statistical analyses of the background corrected image intensitydata for the complete set of array features, thereby determining adynamic image intensity threshold for discrimination between labeled andnon-labeled features of the array, and wherein the one or morestatistical analyses are selected from the list including, but notlimited to, k-means clustering, k-medoids clustering, mixture modelstatistical analysis, or an empirical analysis.

Also disclosed is a mechanism comprising: (a) a closure; (b) a housingwhich magnetically holds the closure in a first position; and (c) atranslation stage which magnetically holds the closure in a secondposition. In some embodiments, the mechanism further comprising a gasketpositioned between the closure and the housing. In some embodiments, thegasket is attached to the closure. In some embodiments, the gasket isattached to the housing. In some embodiments, the closure and housingare substantially opaque, and the gasket creates a substantiallylight-tight seal between the closure and the housing in the firstposition. In some embodiments, one or more magnets are positioned tohold the closure onto the housing in the first position. In someembodiments, one or more magnets are positioned to hold the closure ontoa first surface of the translation stage in the second position. In someembodiments, two or more pairs of mating locating features to align theclosure with the translation stage in the second position. In someembodiments, two or more pairs of mating locating features to align theclosure with the housing in the first position. In some embodiments, thepairs of mating locating features comprise conical pins and conicalholes. In some embodiments, the housing comprises an optical instrument.In some embodiments, the translation stage includes a sample holder. Insome embodiments, the sample holder is designed to hold a microscopeslide, a microarray, or a microwell plate. In some embodiments, theclosure is not hinged. In some embodiments, the closure is not attachedto either the housing or the translation stage through the use offasteners such as screws or clips. In some embodiments, the closure isnot attached to either the housing or the translation stage through theuse of an adhesive.

BRIEF DESCRIPTION OF THE DRAWINGS

The novel features of the invention are set forth with particularity inthe appended claims. A better understanding of the features andadvantages of the present invention will be obtained by reference to thefollowing detailed description that sets forth illustrative embodiments,in which the principles of the invention are utilized, and theaccompanying drawings of which:

FIGS. 1A-1G show one example of an optical system, and componentsthereof. FIG. 1A depicts an isometric projection of the exemplaryoptical system. FIG. 1B depicts a top view of the optical system. FIG.1C depicts a dimetric view of the optical system. FIG. 1D depicts afront view of the optical system. FIG. 1E depicts a side view of theexemplary optical system comprising a single axis stage, an imagingsystem, and an illumination system. FIG. 1F depicts a back view of theoptical system. FIG. 1G depicts components that control the operation ofthe optical system.

FIG. 2 shows an exemplary layout of lenses in an imaging system.

FIG. 3 shows an exemplary layout of lenses in an illumination system.

FIG. 4A shows an array image acquired from the optical instrument. FIG.4B shows a histogram of intensities for individual features.

FIG. 5 shows a feature intensity distribution observed for hybridizationof array probes with labeled target molecules in atitration experiment.

FIG. 6A shows a noisy array image. FIG. 6B shows the intensitydistribution before background adjustment. FIG. 6C shows the intensitydistribution after background adjustment.

FIGS. 7A-7D show external views of instrument designed for digitalcounting of features on arrays. FIG. 7A is an axonometric view of theinstrument as viewed from the upper right. FIG. 7B is an axonometricview of the instrument as viewed from the right-front. FIG. 7C is afront view of the instrument. FIG. 7D is an axonometric view of theinstrument as viewed from the upper left.

FIG. 8 shows an internal view (front view; 3D CAD model) of aninstrument designed for digital counting of features on arrays.

FIG. 9 depicts an internal view (rear view; 3D CAD model) of aninstrument designed for digital counting of features on arrays.

FIG. 10 shows a photograph of a system with the sample loading stage inthe extended (loading) position, having pulled the door away from thefront panel. A Pixel 16 array assembly is shown in the loading tray.

FIG. 11A shows an exploded view of a door assembly that utilizes amagnetic mechanism for positioning a door on a sample compartment stage.FIG. 11B shows another exploded view of the door assembly thatillustrates conical locator features for ensuring proper alignment ofthe door with the stage.

FIG. 12 depicts an exploded view of an upper stage assembly with magnetswhich mate with a corresponding pair of magnets on the door.

FIG. 13 shows an exploded view of a front panel assembly with magnetswhich mate with a corresponding pair of magnets on the door.

FIG. 14 shows the viewing reference orientation for array production andanalysis in one embodiment of an array, showing the 16 array locationson a glass substrate. Nominal dimensions are shown (in millimetres).

FIG. 15 shows the layout of features on one embodiment of an array.Nominal dimensions are shown (in millimetres).

FIG. 16 shows the layout of an array designed for digital counting oftarget molecules in a sample, including the positions of positivecontrols (fiducials), negative controls, and index spots.

FIG. 17A shows an example of an array image after transformation to thereference orientation. FIG. 17B shows the image size (in pixels) and aschematic of feature positions for the two-array image.

FIGS. 18A-B depict software workflows for performing an experiment on aninstrument designed for digital counting of features on arrays. FIG.18A: workflow for a single-axis system with manual sample loading. FIG.18B: workflow for a dual-axis system with automatic sample tray loading.

FIG. 19 depicts an analysis window comprising a 12×12 pixel areaassociated with each feature in the array.

FIG. 20 depicts a map of the pixel designations within the analysiswindow for each feature in the array.

FIG. 21 depicts a scatter plot (upper) of intensity data obtained froman image of an array that illustrates the different categories offeatures identified by the analysis software, and a histogram (lower) ofthe feature intensity data. Dashed lines indicate examples of intensitythresholds determined by the software that are used to discriminatebetween labeled (“on”) and non-labeled (“off”) features.

FIG. 22 depicts a scatter plot (upper) and histogram (middle) of arrayfeature intensity data that illustrate the use of an intensity threshold(dashed lines) that discriminate between labeled (“on”) and non-labeled(“off”) features of an array. In one embodiment of the presentlydescribed analysis methods, the threshold is determined from the maximumslope of a plot of sorted intensity data (lower).

FIG. 23 depicts the results of fitting a 3-component distribution modelused to determine an intensity threshold in one embodiment to a 128-binfeature intensity histogram.

FIG. 24A illustrates deviance calculations for fitting one normaldistribution to histograms of array feature intensity data. FIG. 24Billustrates the deviance calculations for fitting two normaldistributions to histograms of array feature intensity data. In someembodiments, deviance measurement may be used as a quality metric.

FIG. 25 depicts the uncertainties calculated for various methods ofcombining output data from replicate experiments.

FIG. 26 shows dilution series data for using digital counting of labeledfeatures on an array to measure the number of target RNA molecules in asample.

FIG. 27 shows a screenshot of the output data provided by the systemsoftware for a dilution series experiment. For each array used in thedilution series experiment, the software displays a histogram of featureintensity data with a blue line indicating the value of the thresholdused for counting, overlaid on a digital representation of the array.

DETAILED DESCRIPTION OF THE INVENTION

Array technologies have been widely used in biomedical studies for thedetection of biomolecules and profiling of gene expression levels, etc.Arrays are typically comprised of immobilized probes which can bind toor hybridize with target molecules in a sample. Detection of binding orhybridization events is often achieved through the use of optical labels(e.g. fluorophores) and scanning or imaging techniques (e.g.fluorescence scanning or imaging). A feature on an array is a smallregion of immobilized probes that are specific for a given targetmolecule, e.g. probes that hybridize to specific DNA or RNA sequences.Identifying the pattern of labeled features on a hybridized array thusprovides information about the presence of specific molecules, e.g. DNAor RNA molecules in the sample, which in turn can provide valuable datain biomedical studies. Two important engineering requirements forproviding high quality, quantitative data for biomedical investigationsare (i) to correctly image the hybridized arrays, and (ii) to correctlyanalyze the images to extract quantitative data. Existing opticalimaging systems typically image one region of an array at a time, whichcan be a slow process if a number of different regions need to beimaged. In addition, current methods of image analysis typicallydetermine an analog signal intensity level (i.e. a signal that can haveany value between some minimum and maximum values that are determined byvarious instrumental and experimental parameters) for each arrayfeature. Analog intensity level measurements are often subject to avariety of instrumental drift and analysis errors, therefore improvedmethods for determining whether or not target molecules are bound to agiven array feature, and improved methods for transforming that datainto quantitative measures of the number of target molecules present ina sample, are of great importance to expanding the use of arraytechnologies in biomedical applications.

The advantages of the methods, systems, and platforms disclosed hereininclude: (i) simultaneous imaging of multiple regions of an array forhigher throughput image acquisition, and (ii) improved methods forreduction of image data to a digital determination of the presence orabsence of bound target molecules (or target molecule labels) for eachfeature of an array, thereby providing for improved quantitation in sometypes of array experiments, for example, those utilizing a set ofstochastic labels for quantifying the number of target molecules presentin a sample. The use of stochastic labeling techniques is described inU.S. Pat. No. 8,835,358 and PCT application US2011/065291, which areincorporated in their entirety herein by reference. In addition toproviding a means for more quantitative detection of target molecules,the use of stochastic labeling techniques allows for mitigation ofamplification bias in assays involving nucleic acid amplification.

Accordingly, disclosed herein are methods, devices, systems, andplatforms for digital counting of labeled features on arrays comprising:(i) optical instruments configured to form images of one or more regionsof an array, (ii) arrays comprising a plurality of features furthercomprising a plurality of probes, and wherein one or more regions of anarray may comprise one or more sub-arrays, and wherein the arrays orsub-arrays are designed for use with sets of stochastic labels, and(iii) computer implemented methods for receiving input image data;locating array features within array images; correcting the signalintensity values associated with each feature for local backgroundintensity values; determining dynamic signal intensity thresholds forthe one or more array regions by performing statistical analyses of thecorrected signal intensity data for a plurality of features; countingthe number of labeled and non-labeled features on the one or moreregions of the array by comparing corrected signal intensity data forthe features to signal intensity thresholds; and calculating the numberof target molecules in a sample, for one or more target moleculespecies, from the number of labeled and non-labeled features detected onthe one or more regions of the array.

In some embodiments, systems are described which comprise: (i) anoptical instrument (or reader) configured to form images of one or moreregions of an array, (ii) a digital processor configured to performexecutable instructions and store data in memory devices, and (iii)computer code for performing image analysis in order to transform imagedata into a digital count of the number of labeled and non-labeledfeatures on the one or more regions of the array. In some embodiments,the computer code further comprises performing a calculation of thenumber of target molecules in a sample, for one or more target moleculespecies, from the number of labeled and non-labeled features detected onthe one or more regions of the array.

In some embodiments, platforms are described which comprise: (i) arraysdesigned for use in stochastic labeling experiments, wherein the arrayscomprise a plurality of features further comprising a plurality ofprobes, and wherein one or more regions of an array may comprise one ormore sub-arrays, and wherein the arrays or sub-arrays are designed foruse with sets of stochastic labels, (ii) an optical instrument (orreader) configured to form images of one or more regions of an array,(iii) a digital processor configured to perform executable instructionsand store data in memory devices, and (iv) computer code for performingimage analysis in order to transform image data into a digital count ofthe number of labeled and non-labeled features on the one or moreregions of the array. In some embodiments, the computer code furthercomprises performing a calculation of the number of target molecules ina sample, for one or more target molecule species, from the number oflabeled and non-labeled features detected on the one or more regions ofthe array.

In some embodiments, software applications (or computer code products)are described that determine the number of labeled features on an array,wherein the software application includes code for performing one ormore of the following computer implemented methods: (i) receiving inputimage data, (ii) locating array features within array images, (iii)correcting the signal intensity values associated with each feature forlocal background intensity values, (iv) determining dynamic signalintensity thresholds for the one or more array regions by performingstatistical analyses of the corrected signal intensity data for aplurality of features, (v) counting the number of labeled andnon-labeled features on the one or more regions of the array bycomparing corrected signal intensity data for the features to signalintensity thresholds, and (vi) calculating the number of targetmolecules in a sample, for one or more target molecule species, from thenumber of labeled and non-labeled features detected on the one or moreregions of the array.

In some embodiments, computer implemented methods are described forperforming local background correction of array signal intensity data,the methods comprising: (i) centering a predefined data analysis windowon each array feature within a digital image of the array, (ii)calculating mean or median intensity values for signal and backgroundpixels according to a predefined pattern of pixels within or around eacharray feature, and (iii) subtracting the mean or median backgroundintensity from the mean or median signal intensity to determine abackground corrected signal intensity value for each array feature.

In some embodiments, computer implemented methods are described fordetermining dynamic image intensity thresholds from the corrected imageintensity data for a plurality of features on an array, the methodscomprising: (i) collecting image intensity data for each feature of thearray, (ii) optionally performing a local background correction on theimage intensity data for each feature on the array; and (iii) performingone or more statistical analyses of the background corrected imageintensity data for the complete set of array features, therebydetermining a dynamic image intensity threshold for discriminationbetween labeled and non-labeled features of the array. In someembodiments, the one or more statistical analyses are selected from thelist including, but not limited to, k-means clustering, k-medoidsclustering, mixture model statistical analysis, or empirical analysesbased on sorting of image intensity values or pairwise differences inimage intensity values. As used herein, the term “dynamic intensitythreshold” refers to a parameter that is determined based on an analysisof data derived from the experiment in progress. The use of a dynamicimage intensity threshold for discrimination between labeled andnon-labeled features of an array helps to minimize or eliminate errorsin data processing that may arise from instrumental drift orexperimental procedure.

DEFINITIONS

Unless otherwise defined, all technical terms used herein have the samemeaning as commonly understood by one of ordinary skill in the art inthe field to which this disclosure belongs. As used in thisspecification and the appended claims, the singular forms “a,” “an,” and“the” include plural references unless the context clearly dictatesotherwise. Any reference to “or” herein is intended to encompass“and/or” unless otherwise stated.

As used herein, the terms “system” and “platform” are usedinterchangeably. Similarly, the terms “image sensor”, “imaging sensor”,“sensor chip”, and “camera” are used interchangeably to describe twodimensional photosensors used for imaging purposes, and the use of theterms “image intensity” and “signal intensity” are also usedinterchangeably in describing data analysis methods. Finally, unlessotherwise stated, the terms “software”, “software application”,“software module”, “computer program”, and “computer code” are also usedinterchangeably.

Stochastic Labeling Methods

The use of stochastic labeling techniques is described in U.S. Pat. No.8,835,358 and PCT application US2011/065291, which are incorporated intheir entirety herein by reference.

Briefly, high-sensitivity single molecule digital counting may beachieved through the stochastic labeling of a collection of identicaltarget molecules. Each copy of a target molecule is randomly labeledusing a large, non-depleting reservoir of unique labels. The uniquenessof each labeled target molecule is determined by the statistics ofrandom choice, and depends on the number of copies of identical targetmolecules in the collection compared to the diversity of labels. Thesize of the resulting set of labeled target molecules is determined bythe stochastic nature of the labeling process, and analysis of thenumber of labels detected then allows calculation of the number oftarget molecules present in the original collection or sample. When theratio of the number of copies of a target molecule present to the numberof unique labels is low, the labeled target molecules are highly unique(i.e. there is a very low probability that more than one target moleculewill have been labeled with a given label), and the digital countingefficiency is high. This stochastic metholodology transforms the problemof counting molecules from one of locating and identifying identicalmolecules to a series of yes/no digital questions regarding detection ofa set of predefined labels. In some embodiments, the labeled productsare detected by means of DNA sequencing. In other embodiments, thelabeled products for one or more target molecules of choice are detectedwith high specificity using the array readout systems described herein.

Arrays and Features

Disclosed herein are arrays designed for use in stochastic counting ofone or more target molecules in a sample. Arrays provide a means ofdetecting the presence of labeled target molecules, wherein the labelscomprise a large and diverse set of unique labels.

In many embodiments, arrays comprise a plurality of features (or spots)on the surface of a substrate, wherein each feature further comprises aplurality of attached probes. In some embodiments, the array maycomprise one or more regions, each of which may comprise a plurality offeatures or sub-arrays. For example, an array may comprise 2, 3, 4, 5,6, 7, 8, 9, 10 or more regions, or alternatively, an array may comprise15, 20, 25, 30, 35, 40, 45, 50 or more regions. In some embodiments, anarray may comprise 60, 70, 80, 90, 100 or more regions. In otherembodiments, an array may comprise hundreds, thousands, or tens ofthousands of regions.

Non-limiting examples of arrays include microtiter plates, microwellplates, 16-well microscope slides, spotted microarrays, or microarraysfabricated by in situ solid-phase synthesis. A region of an array maycomprise one well of a 16-well microscope slide, one well of aglass-bottomed 96-well plate, or one well of a glass-bottomed 384-wellplate. Alternatively, a region of an array may comprise more than onewell, for example, in some embodiments, a region may comprise 2 adjacentwells, 4 adjacent wells; or a larger number of wells positioned in closeproximity to each other. In some embodiments, the arrays may comprisehigh-density oligonucleotide arrays with more than 1,000 features persquare millimeter, and a region on the array may comprise a selectedarea of the array substrate surface, for example, an area ofapproximately 1 mm×1 mm.

As indicated previously, in many embodiments, the set of probes attachedto a set of features of an array are selected for detection of aspecific set of unique labels designed for use in stochastic labelingstudies. The attachment of the probes to the array substrate may becovalent or non-covalent, and permanent or temporary. A probe may be asequence of monomers including, but not limited to, for example,deoxy-ribonucleotides, ribonucleotides, amino acids, or syntheticmonomers, or they may be a sequence of oligomers, including, but notlimited to, for example, oligonucleotides (e.g. DNA or RNA sequences) orpeptide sequences. In some cases, a probe may be a macromolecule,including but not limited to, for example, antibodies or antibodyfragments. Each feature on an array corresponds to a small area of thearray substrate comprising immobilized probes having the same molecularsequence that bind to or hybridize with the same target molecule. Two ormore features on the array may be identical, similar, or different. Inmany embodiments, arrays will include one or more fiducial marks usedfor alignment or orientation purposes, as well as positive and negativecontrol features in addition to feature sets used for detection of astochastic label set. Positive control features may comprise probes thatbind to or hybridize with molecules known to be always present in asample, or probes that bind to or hybridize with molecules spiked into asample in a controlled fashion. Negative control features may compriseprobes that are specific for molecules that are known to be absent froma sample, or they may comprise features having no probes attached to thesubstrate surface at all.

In many embodiments, the array substrate, also called a support, may befabricated from a number of materials. The materials may be solid. Thematerials may be semi-solid. Examples of materials that may be used tofabricate array substrates include, but are not limited to, glass, fusedsilica, silicon, polymer, or paper.

In some embodiments, the present disclosure also describes arrays foruse in stochastic labeling studies. In particular, arrays are describedwherein the arrays comprise a plurality of features having immobilizedprobes thereon that are complementary to a set of labels designed foruse in stochastic labeling experiments, and wherein there is at leastone feature on the array for every label in the label set. Someembodiments include an array comprising: (a) a plurality of features,optionally organized into a plurality of sub-arrays, wherein theplurality of features comprise: (i) one or more fiducial featurescomprising oligonucleotide probes of a defined fiducial sequence; (ii)one or more positive control features comprising oligonucleotide probesof one or more defined positive control sequences; (iii) one or morenegative control features having no oligonucleotide probes; and (iv) aplurality of label set features comprising oligonucleotide probes,wherein each individual feature comprises a unique sequence selectedfrom a set of label sequences designed for stochastic labeling of one ormore target molecules. In some embodiments, the arrays described in thepresent disclosure comprise oligonucleotide probe sequences comprising25-mers, wherein the 5′ terminus may optionally be labeled with a 6carbon atom amino-modifier. In some embodiments, the arrays described inthe present disclosure further comprise oligonucleotide probescomprising the set of 960 unique oligonucleotide sequences listed inTable 1. In some embodiments, the arrays described in the presentdisclosure comprise a set of olignucleotide probes that are 70%homologous, 80% homologous, 85% homologous, 90% homologous, or 95%homologous with the set of sequences listed in Table 1. In someembodiments, the array described in the present disclosure comprise aset of oligonucleotide probes that includes 10%, 20%, 30%, 40%, 50%,60%, 70%, 80%, or 90% or more of the sequences listed in Table 1.

Hybridization and Detection

In many embodiments of the disclosed methods, systems, and platforms,samples may be processed prior to placing them in contact with theimmobilized probes on arrays. For example, target molecules in thesamples may be labeled with fluorescent dye molecules and/or stochasticlabels during the sample preparation step. Prior to hybridization witholigonucleotide probes, for example, target DNA or RNA molecules may becovalently linked to fluorescent dye molecules including, but notlimited to, fluorescein, Cy3, or Cy5. Alternatively, target moleculesmay be labeled after binding or hybridizing to probes on the array. Forexample, target molecules may be covalently linked to biotin prior tobinding or hybridization with probes on the array. Following the bindingor hybridization step, the immobilized target molecules may then belabeled with streptavidin conjugated to optical tags including, but notlimited to, phycoerythrin, quantum dot nanoparticles, goldnanoparticles, or blue latex beads. There are many methods for labelingtarget molecules, either before or after binding or hybridization to thearray, and many possible choices for suitable optical labels or tags.

Once a sample has been contacted with an array, the array (or one ormore regions of the array) may comprise one or more labeled features.Each region of an array that has been contacted with a sample comprisinglabeled target molecules (where the target molecules are labeled eitherbefore or after contact with the array) may, for example, comprise zero,one, two, or more labeled features. Alternatively, a region of an arraythat has been contacted with a sample may comprise 2, 3, 4, 5, 6, 7, 8,9, 10 or more labeled features. In some embodiments, a region of anarray that has been contacted with a sample may comprise 15, 20, 25, 30,35, 40, 45, 50, or more labeled features. In high-density arrays, aregion of an array that has been contacted with a sample may comprisemore than 100 labeled features, more than 1,000 labeled features, morethan 10,000 labeled features, more 100,000 labeled features, or morethan 1,000,000 labeled features.

Optical Instruments

The methods, systems, and platforms described herein may comprise anoptical instrument used for finite-conjugate digital imaging of one ormore regions of an array, wherein the instrument typically includes anillumination system, an imaging system, and a translation stage. In someembodiments, the instrument operates as a “macroscope” having amagnification of less than one. In other embodiments, the instrumentoperates as a “microscope” having a magnification of greater than one.In still other embodiments, the instrument operates as a “contactimager” having a magnification equal to one. The choice of magnificationwill typically depend on the field of view required to image the regionof interest, and on the size of the image sensor.

By way of non-limiting example, if a region of an array comprises asingle well of a 16-well microscope slide, or a single well of aglass-bottomed 96-well plate, the dimensions of the region to be imagedmay be approximately 7 mm×7 mm, and the pitch (center-to-center distancebetween two adjacent regions of the array may be approximately 9 mm. Insome embodiments, the optical instrument may be used to take an image ofone well at a time, or an image of 2 adjacent wells simultaneously, oran image of 4 (2×2) adjacent wells simultaneously, and the requiredfield of view, or region to be imaged, may be adjusted accordingly.Similarly, the optical instrument may form an image of 6 (3×2 or 2×3), 8(4×2 or 2×4), 9 (3×3), 10 (5×2 or 5×2), or 12 (6×2, 4×3, 3×4, or 2×6)adjacent wells simultaneously.

By way of another non-limiting example, if a region of an array is asingle well of a glass-bottomed 384-well plate, the dimensions of theregion to be imaged may be approximately 3 mm×3 mm, and the pitchbetween two adjacent regions of the array may be approximately 4.5 mm.Again, in some embodiments, the optical instrument may be used to takean image of one well at a time, or an image of 2 adjacent wellssimultaneously, or an image of 4 (2×2), 6 (3×2 or 2×3), 8 (4×2 or 2×4),12 (4×3 or 3×4), or 16 (4×4) adjacent wells simultaneously.

In another non-limiting example, the optical instrument may be used toimage high-density oligonucleotide arrays, for example arrays havingmore than 1,000 features per square millimeter, and a region on thearray may be approximately 1 mm×1 mm in area, for example.

Imaging System

One main component of the optical instrument is an imaging system. Theimaging system may include one or more lenses in addition to a CCD orCMOS camera. Typically the CCD or CMOS camera will have a resolutionbetween a few hundred thousand and a few million pixels. A highresolution camera may have tens of millions of pixels, or more.

The imaging system may be configured to magnify the image of the array.The required magnification of the imaging system can be determined bythe required field of view and by the size of the CCD or CMOS sensor. Byway of a non-limiting example, if the optical instrument is used to takean image of 2 adjacent wells of a 16-well microscope slidesimultaneously, the required field of view is approximately 16 mm×8 mm.If the light-sensitive area of the CCD or CMOS sensor is about 4.8mm×3.6 mm, the instrument is a macroscope and a magnification of about0.3 is required. In this case, only data from the central 4.8 mm×2.4 mmof the sensor would be used.

By way of non-limiting example, an appropriate imaging system with amagnification of 0.3 may be constructed using an achromatic cementeddoublet lens with a focal length of 85 mm and an infinite-conjugatecamera lens with a focal length of 25 mm. If a spectrally selectiveemission filter is used (for example, a single-band interference filter,multi-band interference filter, longpass interference filter, orlongpass colored glass filter), and this filter is typically locatedbetween the achromatic cemented doublet lens and the camera lens.Additional configurations of an imaging system with a magnification of0.3 are possible. For example, the achromatic cemented doublet lens canbe omitted, and a finite-conjugate camera lens can be used instead of aninfinite-conjugate camera lens. In this case, the spectrally selectiveemission filter is preferably located on the long-conjugate side of thecamera lens.

A sensor with a light-sensitive area of 4.8 mm×3.6 mm is known as a⅓-inch format sensor. If a sensor of different size is used, therequired magnification will be different. By way of a non-limitingexample, if the required field of view is 16 mm×8 mm and a sensor havinga light-sensitive area of 6.4 mm×4.8 mm (known as a ½-inch formatsensor) is used, then the required magnification is 0.4. An appropriateimaging system with a magnification of 0.4 can be constructed using, forexample, an achromatic cemented doublet lens with a focal length of 85mm and an infinite-conjugate camera lens with a focal length of 35 mm.

As another non-limiting example, if the dimensions of a region are about0.66 mm×0.66 mm and a sensor with a light-sensitive area of 8.8 mm×6.6mm (known as a ⅔-inch format sensor) is used, then the instrument is amicroscope and the required magnification is about 10. In this case,only data from the central 6.6 mm×6.6 mm of the sensor will be used. Anappropriate imaging system with a magnification of 10 can be constructedusing, for example, an infinite-conjugate microscope objective with afocal length of 20 mm and a microscope tube lens with a focal length of200 mm, with a spectrally selective emission filter typically locatedbetween the microscope objective and the tube lens. Alternatively afinite-conjugate 10 x microscope objective can be used and themicroscope tube lens can be omitted. In this case the spectrallyselective emission filter can be located on the long-conjugate side ofthe microscope objective.

An imaging system of any required magnification can be constructed usinga combination of off-the-shelf and custom optical elements that does notnecessarily include either a camera lens or a microscope objective. Theoptical elements may have various combinations of spherical, flat,aspheric, or diffractive surfaces.

Illumination System

Another main component of the optical instrument is an illuminationsystem. The purpose of the illumination system is to illuminate thearray within the field of view of the CCD or CMOS camera. To reducesensitivity to edge effects and to misalignment, it may be desirable forthe illuminated area to be slightly larger than the camera's field ofview. By way of a non-limiting example, if the field of view is about 16mm×8 mm, a reasonable illuminated area may be about 18 mm×10 mm. Thetypes of illumination may be Abbe, Kohler, or neither Abbe nor Kohlerillumination. Abbe illumination and Kohler illumination are well knownand are described in, for example, Chapter 14 of Optical System Design,Second Edition by Robert E. Fischer et al., SPIE Press, McGraw-Hill,N.Y., 2008.

In some embodiments, the illumination system may be used for off-axisillumination. In other embodiments, the illumination system may be usedfor trans-illumination or epi-illumination. If the illumination systemis used for off-axis illumination or trans-illumination, then theillumination system and the imaging system are separate from each other,with no shared optical components. If the illumination system is usedfor epi-illumination, then the illumination system and the imagingsystem may share a beamsplitter and possibly one or more lenses. Thebeamsplitter may be a plate beamsplitter or a cube beamsplitter. If theoptical instrument is used for fluorescence imaging, the beamsplitter istypically a single-edge or multi-edge longpass dichroic beamsplitter.

Often the illumination system may contain a square or rectangularaperture so that the illuminated area has the same shape as the regionthat is imaged by the CCD or CMOS camera. In embodiments where off-axisillumination is used, the aperture may be trapezoidal in shape insteadof square or rectangular. An off-axis illumination system may or may notsatisfy the Scheimpflug condition. The Scheimpflug condition isdescribed in, for example, Modern Optical Engineering, Second Edition byWarren J. Smith, McGraw-Hill, N.Y., 1990.

In some embodiments, the illumination system may contain one or more ofthe following: spherical lenses, aspheric lenses, a solid homogenizingrod with a rectangular or trapezoidal cross section, a hollowhomogenizing light tunnel with a rectangular or trapezoidal crosssection, a microlens array or a pair of microlens arrays, a stationaryor rotating diffuser, a compound parabolic concentrator, a non-imagingoptical element other than a compound parabolic concentrator (e.g., afree-form catadioptric element), an optical fiber, a fiber bundle, or aliquid light guide.

The illumination system may contain one or more light sources, selectedfrom the group including, but not limited to, one or more LEDs, one ormore lasers, a xenon arc lamp, a metal halide lamp, or an incandescentlamp, or a combination thereof. The illumination system may also containa spectrally selective excitation filter selected from the listincluding, but not limited to, a single-band interference filter, amulti-band interference filter, or a shortpass interference filter. Ifthe illumination system contains two or more light sources, they may bethe same (by way of non-limiting example, two or more LEDs with peakemission wavelengths of about 525 nm for excitation of Cy3 dye, mountedas close together as possible on a circuit board) or different (by wayof non-limiting example, an LED with a peak excitation wavelength ofabout 525 nm for excitation of Cy3 dye, and an LED with a peakexcitation wavelength of about 625 nm for excitation of Cy5 dye, mountedas close together as possible on a circuit board). Two-color ormulticolor LED assemblies are available from, for example, LED Engin,Inc. (San Jose, Calif.) and Innovations in Optics, Inc. (Woburn, Mass.).

In some embodiments, a light source in the illumination system may becontrolled electronically. By way of a non-limiting example, a lightsource may be synchronized with the CCD or CMOS camera so that the lightsource turns on when the CCD or CMOS camera begins an exposure and turnsoff when the camera finishes an exposure. If the illumination systemcontains two or more light sources, they may optionally be controlledtogether or independently of each other.

In some embodiments, a light source may be left on continuously. In thiscase, the illumination system may contain an electronically controlledshutter, and the shutter may be synchronized with the CCD or CMOS cameraso that the shutter opens when the CCD or CMOS camera begins an exposureand closes when the camera finishes an exposure.

In some embodiments, the optical instrument may contain a singleillumination system. In other embodiments, the instrument may containtwo or more illumination systems that are identical. In yet otherembodiments, the instrument may contain two or more illumination systemsthat are different. By way of non-limiting examples, an opticalinstrument for detecting fluorescence from Cy3 and Cy5 may contain oneillumination system for Cy3 excitation and another illumination systemfor Cy5 excitation, or it may contain a single illumination system thatis used for both Cy3 and Cy5 excitation.

Translation Stage

Yet another main component of the optical instrument may be one or moretranslation stages. One purpose of the translation stage may be to movesample holders in and out of the field view of the imaging system.Another purpose of the translation stage system may be to move theimaging system, components of the imaging system, the illuminationsystem, or components of the illumination system relative to the sampleor relative to one another, for obtaining the best possible image.

In many embodiments of the presently disclosed systems, the translationstage may further comprise a sample holder. By way of non-limitingexamples, if the optical instrument is used to take images of 16-wellmicroscope slides, the translation stage contains a slide holder. If theoptical instrument is used to take images of 96-well plates or 384-wellplates, and it contains a plate holder. The slide holder, plate holder,or other array support holder may be mounted on the translation stagesystem in any of a variety of ways known to those skilled in the art.

The translation stage may have one or more axes of motion. By way of anon-limiting example, if the support is a 16-well microscope slide andthe instrument takes images of 2 adjacent wells simultaneously, a singleaxis of motion may be sufficient. By way of another non-limitingexample, if the support is a 96-well plate and the instrument takesimages of 2 adjacent wells simultaneously, then at least 2 axes ofmotion would be required. Additional axes of motion for adjustment offocus and tilt may also be added. If the instrument can take an image ofall of the regions on the support in a single exposure, then thetranslation stage may be omitted in some embodiments of the opticalinstrument.

Housing

The systems and devices described herein can include features forinsuring that the sensors of the device detect appropriate signal. Forexample the systems and devices can include light excluding features.The light excluding features generally reduce unintended signal fromreaching light sensitive sensors. In many embodiments, one or more ofthe imaging system, illumination system, translation stage, and othercomponents of the instrument are surrounded by a housing. The housingcan be opaque. The housing can, in some instances, act as a faradaycage. In some instances a single housing is sufficient to exclude lightfrom systems. The single housing can also provide external protection ofthe system. Alternatively, multiple housings may individually containone or more components of the instrument. In some instances the housingsare nested housings. In various embodiments, the housing can be gasand/or liquid tight.

The housing may have an access point which can exclude light from theinterior of the housing. The access point may comprise materials thatabsorb light in the spectrum relevant to the sensors within the housing,e.g. vantablack in the visible spectrum. The access point may comprise aclosure device. The closure device may be opaque. The closure device maybe, e.g., a door. The closure device may be substantially light-tight ina closed position. The closure may be light-tight in a closed position.

The closure device can be opened, e.g., for insertion and removal of a16-well slide, 96-well plate, 384-well plate, or other array support. Asensor (for example, a photointerrupter) may be used to determinewhether the closure device is open or closed. The instrument's softwareor electronic hardware may prevent the light source in the illuminationsystem from turning on when the closure device is open, may preventpower from being applied to the image sensor, and/or may prevent thetranslation stage from moving when the closure device is open.

In some embodiments, the housing may further comprise a mechanism forautomated opening and closing of the closure device, as illustrated inFIGS. 10-13. The closure device can provide access to the interior ofthe housing. The closure device can provide access for the array to beloaded in and out of the instrument. This operation can be performedautomatically. In some instances, the closure device can exclude ambientlight during imaging, while opening reliably to permit loading.

In some instances the closure device does not comprise pivoting parts.In some embodiments of the disclosed systems and platforms, the closuredevice is held by magnets to the housing. Magnets can hold the closuredevice to the housing in a closed position. Magnets can hold the closuredevice to a loading device, e.g. a tray, in an open position. During atransition from an open to closed position the closure device cantransition from being primarily magnetically attached to a loadingdevice to being primarily magnetically attached to the housing. During atransition from a closed to open position the closure device cantransition from being primarily magnetically attached to the housing tobeing primarily magnetically attached to the loading device. In someinstances the transition between the open and closed state ismagnetically unstable, such instability causing the closure device tomove from the transition state to either the more stable open or closedposition.

The closure device can comprise a self-locating function provided byconical features on the door. The thicknesses of the parts which supportthe magnets on each side of a mating pair, and the depth of retainingpockets within those parts, defines the spacing between magnets in eachmating pair, and thus the holding forces. The design geometry is matchedto the power of the motors to provide enough retaining force, withoutrequiring high motor torque. The system is further designed such thatthe motor current and speed (and hence torque) can be controlled toimprove the performance, and avoid creating a safety hazard. Two of thefour magnet pairs are used to temporarily hold the door to the front ofthe sample tray, when the tray moves outward for loading an arrayassembly, as depicted in FIG. 10. The other two magnet pairs are used tohold the door closed against the front panel, after the tray has movedinwards (and separated the other two magnet pairs in the process). Therespective allocation of magnets is shown in FIG. 11A. The matingmagnets on the front of the stage are shown in FIG. 12. The locations ofthe mating magnets in the front panel are shown in FIG. 13. To providefor secure grip (and therefore reliable operation), rare earth magnetsprovide high strength (e.g. neodymium magnets). Some embodiments of thedesign call for disc magnets approximately 8 mm in diameter and 3 mmthick, with the magnetic field parallel to the axis. In someembodiments, it is sufficient to replace one magnet from each pair witha weaker magnet, or with a piece of magnetic material such as iron ormild steel.

In some embodiments of the systems and platforms disclosed herein, amechanism for providing for automated door or lid closure on one or moreinstrument compartments is provided, wherein the mechanism comprises:(a) a closure; (b) a housing which magnetically holds the closure in afirst position; and (c) a translation stage which magnetically holds theclosure in a second position. In some embodiment, the mechanism furthercomprises a gasket positioned between the closure and the housing. Insome embodiments of the mechanism, the gasket is attached to theclosure. In other embodiments, the gasket is attached to the housing. Insome embodiments, the closure and housing are substantially opaque, andthe gasket creates a substantially light-tight seal between the closureand the housing in the first position. In some embodiments of themechanism, one or more magnets are positioned to hold the closure ontothe housing in the first position. In some embodiments of the mechanism,one or more magnets are positioned to hold the closure onto a firstsurface of the translation stage in the second position. In someembodiments, the mechanism further comprises two or more pairs of matinglocating features to align the closure with the translation stage in thesecond position. In some embodiments, the mechanism further comprisestwo or more pairs of mating locating features to align the closure withthe housing in the first position. In some embodiments of the mechanism,the pairs of mating locating features comprise conical pins and conicalholes. In some embodiments, the housing comprises an optical instrument.In some embodiments, the translation stage includes a sample holder. Insome embodiments, the sample holder is designed to hold a microscopeslide, a microarray, or a microwell plate. In some embodiments, theclosure is not hinged. In some embodiments, the closure is not attachedto either the housing or the translation stage through the use offasteners such as screws or clips. In some embodiments, the closure isnot attached to either the housing or the translation stage through theuse of an adhesive.

Image Data

The methods, systems, and platforms described herein for counting one ormore labeled features on an array may comprise data input, or use of thesame. The data input may comprise imaging information and/or images ofone or more regions of arrays. The images comprise pixel data, whereineach unit of pixel data may be encoded in, by way of non-limitingexamples, 4, 8, 12, 14, 16, 32, 64, 128, 256, or more bits. An image mayencompass one or more regions of an array. The spatial resolution of animage may be determined by the spatial resolution of the opticalinstrument, but in some embodiments of the disclosed methods andsystems, spatial resolution may be enhanced by digital image processingschemes based on, by way of non-limiting examples, interpolations,extrapolations, modeling, and/or transforms.

The methods, systems, and platforms described herein for counting one ormore labeled features on an array may comprise acquisition and analysisof images of one, two, or more distinct regions on an array. In someembodiments, two or more regions to be imaged may overlap, partiallyoverlap, or not overlap at all. Furthermore, two or more regions to beimaged may be adjacent, or non-adjacent.

The methods, software, systems, and platforms described herein forcounting one or more labeled features on an array may compriseacquisition and analysis of images of all or a portion of an array. Insome embodiments, the region of an array that is imaged may comprise atleast about 1% of the total area of the array. In some embodiments, theregion of the array that is imaged image may comprise at least about 2%,3%, 4%, 5%, 6%, 7%, 8%, 9%, 10% or more of the total area of the array.In other embodiments, the region of the array to be imaged may compriseat least about 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%,22%, 23%, 24%, 25% or more of the total area of the array. In stillother embodiments, the region of the array to be imaged may comprise atleast about 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70% or more of thetotal area of the array. In some embodiments, the region of the array tobe imaged may comprise at least about 75%, 80%, 85%, 90%, 92%, 95%, 97%or more of the total area of the array.

The methods, software, systems, and platforms described herein forcounting one or more labeled features on an array may compriseacquisiton and analysis of images of all or a portion of the features ofan array. In some embodiments, the image may encompass between 10% and100% of the total number of features on the array. In some embodiments,the image may encompass at least 5%, at least 10%, at least 20%, atleast 30%, at least 40%, at least 50%, at least 60%, at least 70%, atleast 80%, at least 90%, or at least 95% of the total number of featureson the array. In some embodiments, the image may encompass at most 95%,at most 90%, at most, 80%, at most 70%, at most 60%, at most 50%, atmost 40%, at most 30%, at most 20%, at more 10%, or at most 5% of thetotal number of features on the array. The number of featuresencompassed by the image may fall within any range bounded by any ofthese values (e.g. from about 15% to about 90% of the total number offeatures of the array).

Image Acquisition

The methods, systems, and platforms described herein comprise softwarefor acquiring images from an optical instrument. In some embodiments,e.g. for optical instruments comprising two or more image sensors, theimage acquisition may operate in a parallel mode, i.e. where two or moreimages are acquired simultaneously. Alternatively, the image acquisitionmay operate in a serial mode, where two or more images are acquiredsequentially. In general, image acquisition may be performed in acontinuous fashion (i.e., wherein the image is acquired within a singleexposure time period) or intermittently (i.e., wherein the image isacquired in a discontinuous fashion, e.g. using two or more separateexposure time periods, wherein in some embodiments two more more imagesare combined for signal averaging purposes).

In a non-limiting example, an array may comprise 16 wells where an imageis formed for each well. The image acquisition module may sequentiallyread the 16 images. Reading the 16 images can be completed in acontinuous time period; or, the system may read a first image followedby analyzing the first image, and then the procedure of image readingand image analysis repeats till the 16th image is analyzed.Alternatively, the image acquisition module may read a pair of images atonce, and repeat the reading till all the 16 images are acquired. The 16images may be read sequentially in a single time period. In someapplications, a pair of images may be read, followed by immediate imageanalyses.

Image Analysis

In general, one of the objectives in performing image processing andanalysis is to improve signal-to-noise ratios and quantitation. In anideal array experiment, labeled features comprising bound targetmolecules and/or labels would produce a uniform, non-saturated signallevel when imaged and non-labeled features would appear uniformly dark,with a signal level of close to zero. In reality, a variety of artifactsdue to instrumental and/or assay procedural issues including, but notlimited to, stray light, background fluorescence (in the case offluorescence-based imaging), particulate contaminants, and non-specificbinding of assay components, can produce images that hinder one'sability to extract quantitative signal intensity data and makedefinitive calls as to which features of the array are labeled.Accordingly, the methods, systems, and platforms disclosed herein maycomprise software for performing a variety of image processing tasksincluding, but not limited to, feature location, image orientationcorrection, background correction, intensity measurement, data scaling,data thresholding, and data analysis functions.

Image orientation and location of features. In some embodiments,fiducial features incorporated into the design of an array are used toorient the image and locate features in an automated fashion usingcustom image analysis software. By way of non-limiting example, themicroarray pattern shown in FIGS. 15 and 16 consists of a 32×32 array offeatures, where fiducial features in the top and bottom rows permitlocation of the array in the digital images. The fiducial features aretypically arranged in an asymmetric pattern whose orientation is readilyidentifiable, e.g. fiducial features located in the top row of featuresin an array such as that depicted in FIG. 16 may comprise a distinctivepattern for which the left and right ends of the row are asymmetric,while the pattern of fiducial features in the bottom row is typicallydifferent from that in the top row. This permits easy manual andautomatic identification of incorrect placement of the array, and alsofacilitated detection of imaging problems. In some embodiments, theimage may be transformed also transformed so that the apparentorientation of the images corresponds to the orientation as viewed by auser, often referred to as the viewing reference orientation, as shownin FIG. 14 for a specific embodiment of an array designed for use withthe methods, systems, and platforms disclosed herein.

Refinement of feature locations. In some embodiments, the measuredlocation of each feature is refined so as to account for arrayfabrication errors, which can produce offsets of several image pixels.The locations of features obtained during the initial image orientationand feature location step may be used to subdivide the array or arrayregion into analysis windows, for example an array may be divided into32×32 analysis windows, wherein each analysis window comprises an imagearea of 12×12 pixels centered on each feature, as shown in FIG. 19. Thesize of the analysis window used is dependent on the size of thefeatures on the array, and may be any size that is necessary tocorrectly locate and distinguish between features and background regionson the array. By way of non-limiting examples, the analysis window maybe defined as a 5×5, 7×7, 9×9, 15×15, 51×51, or 101×101 pixel area thatis centered on the array feature. The position of the feature within thewindow may be determined on the basis of the signal intensitydistribution and clustering of the pixels within the analysis window.The refined location of the feature is calculated as an offset incoordinates X and Y from the site predicted by a perfect rectilineargrid. In some embodiments, distortion of the feature location resultsdue to defects such as dust is avoided by making use of the correlationbetween printing artifacts between different arrays on the samesubstrate. Since the printing artifacts are typically consistent, thecorrection relative to a hypothetical rectilinear grid is alsoconsistent. The feature location optimization results for a givenfeature are combined across all of the arrays being analyzed, and themedian offset is used for subsequent analysis, which greatly decreasesnoise in the final experimental results.

Local background correction. Once the feature pixel set “S” andbackground pixel set “B” have been defined for each location in thearray (for example, see FIG. 20), the local background is removed via acalculation involving signal intensity and background intensitystatistics. Examples of suitable signal and background intensitystatistics for use in local background correction calculations include,but are not limited to, the mean, the median, or a ratio ofsignal-to-background. In some embodiments, following feature locationrefinement performed as described above, the pixels within the analysiswindow are assigned to be signal pixels, background pixels, ortransitional pixels, i.e. pixels to be disregarded, in subsequentcalculations of signal and background intensity statistics (see FIG.20). In some embodiments of the disclosed methods, local backgroundcorrection is performed via subtraction in logarithm space, i.e. acalculation that is closely related to a signal-to-background ratiocalculation, as illustrated in a non-limiting example below:

Given the 16-bit pixel data measurements for a defined feature andbackground area, on next calculates a single value S for the signalpixels and a value B for the background pixels respectively. One usefulstatistic is the median value for each set of pixels, i.e.

-   -   S=the median of the pixel values for the set of pixels “S”    -   B=the median of the pixel values for the set of pixels “B”        Various other statistics could be used in this situation, such        as the mean of the set of values, or a nominated percentile        within the set. It is not necessary, and may not be optimal, to        use the same statistic for both S and B. For example, low data        noise and strong separation between “on” and “off” data points        can be obtained by using:    -   S=the median of the pixel values for the set of pixels “S”, and    -   B=the 25^(th) percentile of the pixel values for the set of        pixels “B”.        As a further enhancement, the particular percentile used can be        a pre-stored and re-configurable parameter stored in a settings        file.        The background-corrected intensity statistic for each spot is:

I=log₂(16 S )−log₂(16 B )

An example of a scatter plot (intensity statistic vs feature number) andhistogram of intensity data are shown in FIG. 21. In this example, thebackground is corrected for by performing a subtraction of logarithms,such that the intensity metric is related to a ratio of S and B. In somesituations, a linear subtraction (e.g. I= S− B) is preferable. Once thebackground-corrected intensity statistics have been calculated for thecompete set of features, the next task is to determine which of thefeatures are labeled (i.e. “on”, or “positive”) and which arenon-labeled (i.e. “off” or “negative”). This is accomplished bydetermining a signal intensity threshold value based on a statisticalanalysis of the local background-corrected feature intensities, andsubsequently counting how many features, k, have background-correctedsignal intensities that are larger than this threshold level. The signalintensity threshold may be considered a “dynamic” signal intensitythreshold in that the threshold is determined through analysis of thedata from the current experiment, and thereby eliminates potentialerrors due to such factors as instrumental drift and variations in assayprocedure.

Determination of dynamic signal intensity thresholds. In manyembodiments of the methods, systems, and platforms disclosed herein, adynamic signal intensity threshold is determined for one or more regionsof an array by performing one or more statistical analyses of thebackground corrected signal intensity data for the complete set offeatures. Any of a variety of statistical (or empirical) analysistechniques may be used, including but not limited to, k-meansclustering, k-medoids clustering, mixture model statistical analysis,probe reference distribution methods, or empirical analysis based onsorting of background corrected signal intensity values, sorting ofpairwise differences in background corrected signal intensity values,etc. In some embodiments, analyses may utilize spatial and/or temporalinformation collected across multiple analysis windows, across multiplearray regions, or over specified periods of time, or combinationsthereof, to improve the quality of the analysis and thereby improve thequantitative aspects of the disclosed methods. In some embodiments,other sources of information, including, but not limited to, forexample, locations of probes, frequently occurring artifact patterns,previously derived results, literature reports, array manufacturers'suggestions, human knowledge, and/or human guidance may also beintegrated into the analysis.

By way of a non-limiting example of threshold determination, in someembodiments of the disclosed methods, the background corrected signalintensity threshold may be determined using an empirical approach (e.g.the “E-Derivative” approach; see FIG. 22) wherein the backgroundcorrected signal intensity data for the complete set of array featuresconstitutes a set I={I_(i)}. The set I is sorted in increasing order toobtain a set of ordered corrected signal intensity valuesz={z_(i)}={Sort[y_(i)]}. Next, the differences between each sorted arrayvalue are calculated to obtain d={d₁, d₂, . . . , d_(m)}, whered_(i)=z_(i+1)−z_(i). The intensity differences are then smoothed using a“window” whose width is w, to produce a smoothed, sorted array s:

$s_{j} = \frac{\sum\limits_{i = {j - w}}^{j + w}d_{i}}{{2\; w} + 1}$

The threshold is T, the point for which the slope of the smoothed,sorted data is steepest (see FIG. 21):

T=max(s _(j))

The number of features, k, which are “on” (or labeled) is:

k=Σ _(i=1) ^(m) l[l _(i) >T].

By way of another non-limiting example of threshold determination, insome embodiments the background corrected signal intensity threshold maybe determined by fitting the background corrected feature intensity datato two more more assumed distributions (i.e. a “Mixture Model”approach), wherein the assumed distributions comprise normaldistributions, uniform distributions, etc. The mixture model approachessentially models the underlying process that generated the data, byassuming that the positive feature intensities are generated from apositive feature distribution with higher average signal intensity, andthe negative feature intensities are generated from a negative featuredistribution with lower average signal intensity. This approachadditionally models the variability in the feature intensities generatedby each distribution, which can be useful in cases where the negativefeature intensities tend to be much less variable, while the positivefeature intensities tends to be much more variable. The choice of thedistributions is determined by the shape of the data curve in abackground corrected feature intensity histogram. The parameters of themodel, e.g. the estimated average intensities for “on” and “off”features and their corresponding variance, are estimated from the datausing a method such as the Expectation Maximization algorithm.

By way of another non-limiting example of threshold determination, insome embodiments the background corrected signal intensity threshold maybe determined by fitting the background corrected feature intensity datato a model function comprising three assumed distributions (i.e. a“3-Component Model” approach), wherein the assumed distributionscomprise a log-normal distribution, Dist1, for the “off” spots, a normaldistribution, Dist2, for the “on” spots, and a flat offset FlatLevel.Adjustable parameters for the model include: (i) the number of bins inthe starting histogram, (ii) Dist1 amplitude, (iii) Dist1 position, (iv)Dist1 standard deviation, (v) Dist2 amplitude, (vi) Dist2 position,(vii) Dist2 standard deviation, and (viii) FlatLevel. An example fit tohistogram data is shown in FIG. 23. One non-limiting example of a methodto determine the threshold after fitting feature intensity data to sucha distribution is as follows: (i) fit the 3-component distribution tothe histogram data, and (ii) set the threshold T by calculating thefollowing values: (1) the intensity t_(low) where the high-intensityside of the fitted log-normal distribution component drops below 1 (or adefined parameter for comparison), (2) the intensity t_(subflat) wherethe high-intensity side of the fitted log-normal distribution componentdrops below the fitted FlatLevel result, (3) the intensity t_(subnorm)where the high-intensity side of the fitted log-normal distributioncomponent drops below the value of the fitted normal distribution atthat histogram bin, and (4) choosing T=min[t_(low), t_(subflat),t_(subnorm)]. Alternative approaches for determining a threshold using a3-component model approach will be apparent to those of skill in theart. It can be beneficial to calculate starting values of modelparameters, to improve the speed and reliability of the modellingprocess, which can be achieved using methods such as a coarse search toidentify the dominant peaks in the histogram, or based on assumptionsderived from typical historical data sets.

By way of another non-limiting example of threshold determination, insome embodiments the background corrected signal intensity threshold maybe determined using a “Peak Split Fiducials” approach. This approach,which copes well with low-quality data, is described as follows. Aninitial split of the feature intensity data into high and low intensitygroups is made using the scale defined naturally by the spread between“on” (label present) and “off” (label absent) features in the fiducialrows. Then, the histogram peak (after optionally smoothing the datausing standard methods such as a moving average filter) is found foreach group. The threshold is then determined by examining the spread inthe intensity data around the low-intensity group peak. Define upper andlower bounds of fiducial intensity: (i) F_(off)=[median of OFFfiducials], F_(on)=[median of ON fiducials], and (iii)F_(range)=F_(on)−F_(off). Perform an initial split of the data based onthe fiducial scale, at the level Splitvalue=F_(off)+PeakSplit×F_(range),where the parameter PeakSplit is a percentage of F_(range). Find 2peaks: (i) Peak4=the intensity peak for which the histogram is amaximum, for all features of intensity less than Splitvalue, (ii)Peak2=the intensity peak for which the histogram is a maximum, for allfeartures of intensity greater than Splitvalue. Calculate the standarddeviation, Stdev1, of all the features in the neighbourhood of Peak1,defined as all index features from the lowest intensity up toPeak1+PeakOffsetFraction×(Peak2−Peak1), where PeakOffsetFraction is anadjustable parameter. Set the threshold to the lesser of T_(psf) andT_(LocMin), which are calculated as follows: (i)T_(psf)=Peak1+StdevMultiple×Stdev1, where StdevMultiple is a parameter,OR T_(LocMin)=the intensity corresponding to the minimum of a smoothedhistogram curve between Peak1 and T_(psf). Similar approaches usingdifferent methods for determining the spread around either peak can alsobe used.

The methods and systems disclosed herein may comprise detecting one ormore labeled features within one or more regions on an array. In someembodiments, detecting a labeled feature within a region may comprisecomparing the background corrected signal intensity for a feature with adynamic signal intensity threshold derived through statistical analysisof the background corrected signal intensities for the complete set offeatures. When the background corrected signal intensity for a givenfeature is above the threshold, the feature may be classified as alabeled feature. Alternatively, if the background corrected signalintensity for a given feature is below the threshold, the feature may beclassified as non-labeled. Application of a background corrected signalintensity threshold to the corrected signal intensity data for thecomplete set of features thus constitutes a binary transformation of thedata to a digital output wherein features are classified as eitherlabeled (“on”) or non-labeled (“off”). Those of skill in the art willrecognize that there are many possible variations in the type and orderof analysis steps that may be applied to achieve this binarytransformation.

Calculation of the absolute number of target molecules in a sample. Theabsolute number of target molecules in a sample, wherein the targetmolecules have been labeled in a stochastic fashion as describedpreviously, may be determined using arrays comprising feature setscomprising probes that are specific for the labels in the stochasticlabel set. Following hybridization or binding of the target molecules orlabeled target molecules to the array, the array is imaged and processedas described above, and the number of target molecules, N, in the sampleis determined from the number, k, of labeled features based on Poissondistribution statistics:

$N = {{- m}*{\log \left( {1 - \frac{k}{m}} \right)}}$

where m is the total number of features (i.e. the total number of uniquelabels in the set of stochastic labels).

Quality metrics. In some embodiments, it is beneficial to include anumerical measure of the quality of the data, to help to gauge thesuccess of an experiment. In some embodiment, this quality measurementmay be based on statistics from the feature-by-feature intensity data.One simple quality measurement Q_(Sep1) is simply the difference betweenthe means of the positive and negative features intensities, afterbackground correction and scaling, i.e. Q_(Sep1)=(mean intensity offeatures having an intensity above the signal intensity threshold)−(meanintensity of features having an intensity below the threshold). In someembodiments, this metric may also incorporate the spread in theintensities of the feature distribution(s) by scaling the differencebetween means by the standard deviation of each distribution, e.g.Q_(Sep2)=Q_(Sep1)/(standard deviation of intensities for feature havingintensities below the threshold intensity). Other quality measurementscan be constructed based on the separation and breadth of modelleddistributions which are fitted to the experimental data. In someembodiments, deviance measurement may be used for a quality metric (FIG.24); this is a calculation based on the degree of separation between twofitted normal distributions. In some embodiments, it is preferable toempirically determine a dynamic intensity threshold by setting thethreshold to a value which maximizes a quality metric.

Confidence intervals. In some embodiments of the methods disclosedherein, it is beneficial to define confidence intervals (see Dube, etal. (2008), PLoS ONE 3(8): e2876 for a more complete description) whenspecifying estimates of the absolute number of target molecules detectedin a sample using the techniques described above. The 95% confidenceinterval of the estimation of N from stochastic labeling experiments canbe derived from k for a single reaction employing a single set of _(m)distinct labels. The 95% confidence interval for N ranges from M_(low)to N_(high), where

${N_{low} = {{- m} \times {\ln\left\lbrack {1 - \left( {\frac{k}{m} - {1.96\sqrt{\frac{\frac{k}{m}\left( {1 - \frac{k}{m\;}} \right)}{m}}}} \right)} \right\rbrack}}},{and}$$N_{high} = {{- m} \times {\ln\left\lbrack {1 - \left( {\frac{k}{m} + {1.96\sqrt{\frac{\frac{k}{m}\left( {1 - \frac{k}{m}} \right)}{m}}}} \right)} \right\rbrack}}$

Ratio of the number of copies of a target molecule in two samples.Frequently, researchers seek to compare the expression levels of genesin different samples, by calculating a ratio between gene expressionlevels in two or more samples. Using calculations such as thosedescribed above, it is possible to derive confidence intervals for suchratios where the number of target molecules in each sample aredetermined using the methods, systems, and platforms as disclosedherein.

Replicate experiments. The benefit of performing replicate experiments,and the proper calculation of associated uncertainties, is illustratedin FIG. 25. While results (blue points) from replicate experiments cansimply be combined (blue error bars), calculating the uncertainty fromPoisson statistics, wherein one considers the replicates as comprising alarger pool of labels, gives the smaller green error bars illustrated inthe figure. The accuracy of this estimation will vary depending on theconsistency between replicates, and there is a numerical simplificationemployed in considering the labels of replicate experiments to be a poolof diverse labels. Therefore, in some embodiments of the disclosedmethods, different methods for calculating confidence intervals may bemore appropriate at high ratios of k/m.

User Interface

The methods, software, systems, and platforms disclosed herein maycomprise a user interface, or use of the same. The user interface mayprovide one or more inputs from a user. The input from the userinterface may comprise instructions for counting the one or more labeledfeatures in a real time mode. The input from the user interface maycomprise instructions for counting the one or more features from one ormore images. The one or more images may be archived images. The one ormore images may be live captured images.

Different platform operators may have their own preferences about thetiming to analyze images. One platform operator may want to run theimage analyses while live capturing images. Another platform operatormay run the image analyses after all the images have been collected. Or,another platform operator may run the image analyses on a set ofarchived images. These options can be selected via inputs to the userinterface.

Digital Processing Device

The methods, software, systems, and platforms disclosed herein maycomprise a digital processing device, or use of the same. The digitalprocessing device may comprise one or more hardware central processingunits (CPU) that carry out the device's functions. The digitalprocessing device may comprise an operating system configured to performexecutable instructions. The digital processing device may be connectedto a computer network. The digital processing device may be connected tothe Internet such that it accesses the World Wide Web. The digitalprocessing device may be connected to a cloud computing infrastructure.The digital processing device may be connected to an intranet. Thedigital processing device may be connected to a data storage device.

Suitable digital processing devices may include, by way of non-limitingexamples, server computers, desktop computers, laptop computers,notebook computers, sub-notebook computers, netbook computers, netpadcomputers, set-top computers, handheld computers, Internet appliances,mobile smartphones, tablet computers, personal digital assistants, videogame consoles, and vehicles. In some instances, smartphones may besuitable for use in the system described herein. In some instances,select televisions, video players, and digital music players withoptional computer network connectivity may be suitable for use in thesystem described herein. Suitable tablet computers may include thosewith booklet, slate, and convertible configurations, known to those ofskill in the art.

The digital processing device may comprise an operating systemconfigured to perform executable instructions. The operating system maybe software, including programs and data, which manages the device'shardware and provides services for execution of applications. Suitableserver operating systems may include, by way of non-limiting examples,FreeBSD, OpenBSD, NetBSD®, Linux, Apple® Mac OS X Server®, Oracle®Solaris®, Windows Server®, and Novell® NetWare®. Suitable personalcomputer operating systems may include, by way of non-limiting examples,Microsoft® Windows®, Apple® Mac OS X®, UNIX®, and UNIX-like operatingsystems such as GNU/Linux®. The operating system is provided by cloudcomputing. Suitable mobile smart phone operating systems may include, byway of non-limiting examples, Nokia® Symbian® OS, Apple® iOS®, ResearchIn Motion® BlackBerry OS®, Google® Android®, Microsoft® Windows Phone®OS, Microsoft® Windows Mobile® OS, Linux®, and Palm® WebOS®.

The digital processing device may comprise a storage and/or memorydevice. The storage and/or memory device may be one or more physicalapparatuses used to store data or programs on a temporary or permanentbasis. The digital processing device may be a volatile memory and mayrequire power to maintain stored information. The digital processingdevice may be a non-volatile memory and may retain stored informationwhen the digital processing device is not powered. The non-volatilememory may comprise flash memory. The non-volatile memory may comprisedynamic random-access memory (DRAM). The non-volatile memory maycomprise ferroelectric random access memory (FRAM). The non-volatilememory may comprise phase-change random access memory (PRAM). Thestorage device may include, by way of non-limiting examples, CD-ROMs,DVDs, flash memory devices, magnetic disk drives, magnetic tapes drives,optical disk drives, and cloud computing based storage. The storageand/or memory device may be a combination of devices such as thosedisclosed herein.

The digital processing device may comprise a display. The display may beused to send visual information to a user. The display may be a cathoderay tube (CRT). The display may be a liquid crystal display (LCD). Thedisplay may be a thin film transistor liquid crystal display (TFT-LCD).The display may be an organic light emitting diode (OLED) display. TheOLED display may be a passive-matrix OLED (PMOLED) or active-matrix OLED(AMOLED) display. The display may be a plasma display. The display maybe a video projector. The display may be a combination of devices suchas those disclosed herein.

The digital processing device may comprise an input device to receiveinformation from a user. The input device may be a keyboard. The inputdevice may be a pointing device including, by way of non-limitingexamples, a mouse, trackball, track pad, joystick, game controller, orstylus. The input device may be a touch screen or a multi-touch screen.The input device may be a microphone to capture voice or other soundinput. The input device may be a video camera to capture motion orvisual input. The input device may be a combination of devices such asthose disclosed herein.

Non-Transitory Computer Readable Storage Medium

The methods, software, systems, and platforms disclosed herein maycomprise one or more non-transitory computer readable storage mediaencoded with a program including instructions executable by theoperating system of an optionally networked digital processing device. Acomputer readable storage medium may be a tangible component of adigital processing device. A computer readable storage medium may beoptionally removable from a digital processing device. A computerreadable storage medium may include, by way of non-limiting examples,CD-ROMs, DVDs, flash memory devices, solid state memory, magnetic diskdrives, magnetic tape drives, optical disk drives, cloud computingsystems and services, and the like. The program and instructions may bepermanently, substantially permanently, semi-permanently, ornon-transitorily encoded on the media.

Computer Programs (General)

The methods, software, systems, and platforms disclosed herein maycomprise at least one computer processor, or use of the same. Thecomputer processor may comprise a computer program. A computer programmay include a sequence of instructions, executable in the digitalprocessing device's CPU, written to perform a specified task. Computerreadable instructions may be implemented as program modules, such asfunctions, features, Application Programming Interfaces (APIs), datastructures, and the like, that perform particular tasks or implementparticular abstract data types. A computer program may be written invarious versions of various languages.

The functionality of the computer readable instructions may be combinedor distributed as desired in various environments. A computer programmay comprise one sequence of instructions. A computer program maycomprise a plurality of sequences of instructions. A computer programmay be provided from one location. A computer program may be providedfrom a plurality of locations. A computer program may include one ormore software modules. A computer program may include, in part or inwhole, one or more web applications, one or more mobile applications,one or more standalone applications, one or more web browser plug-ins,extensions, add-ins, or add-ons, or combinations thereof.

Web Applications

A computer program may include a web application. In light of thedisclosure provided herein, those of skill in the art will recognizethat a web application may utilize one or more software frameworks andone or more database systems. A web application may be created upon asoftware framework such as Microsoft®.NET or Ruby on Rails (RoR). A webapplication may utilize one or more database systems including, by wayof non-limiting examples, relational, non-relational, feature oriented,associative, and XML database systems. Suitable relational databasesystems may include, by way of non-limiting examples, Microsoft® SQLServer, mySQL™, and Oracle®. Those of skill in the art will alsorecognize that a web application may be written in one or more versionsof one or more languages. A web application may be written in one ormore markup languages, presentation definition languages, client-sidescripting languages, server-side coding languages, database querylanguages, or combinations thereof. A web application may be written tosome extent in a markup language such as Hypertext Markup Language(HTML), Extensible Hypertext Markup Language (XHTML), or eXtensibleMarkup Language (XML). A web application may be written to some extentin a presentation definition language such as Cascading Style Sheets(CSS). A web application may be written to some extent in a client-sidescripting language such as Asynchronous Javascript and XML (AJAX),Flash® Actionscript, Javascript, or Silverlight®. A web application maybe written to some extent in a server-side coding language such asActive Server Pages (ASP), ColdFusion®, Perl, Java™, JavaServer Pages(JSP), Hypertext Preprocessor (PHP), Python™, Ruby, Tcl, Smalltalk,WebDNA®, or Groovy. A web application may be written to some extent in adatabase query language such as Structured Query Language (SQL). A webapplication may integrate enterprise server products such as IBM LotusDomino. A web application may include a media player element. A mediaplayer element may utilize one or more of many suitable multimediatechnologies including, by way of non-limiting examples, Adobe® Flash®,HTML 5, Apple® QuickTime®, Microsoft® Silverlight®, Java™, and Unity

Mobile Applications

A computer program may include a mobile application provided to a mobiledigital processing device. The mobile application may be provided to amobile digital processing device at the time it is manufactured. Themobile application may be provided to a mobile digital processing devicevia the computer network described herein.

A mobile application may be created by techniques known to those ofskill in the art using hardware, languages, and development environmentsknown to the art. Those of skill in the art will recognize that mobileapplications may be written in several languages. Suitable programminglanguages include, by way of non-limiting examples, C, C++, C#,Featureive-C, Java™, Javascript, Pascal, Feature Pascal, Python™, Ruby,VB.NET, WML, and XHTML/HTML with or without CSS, or combinationsthereof.

Suitable mobile application development environments may be availablefrom several sources. Commercially available development environmentsinclude, by way of non-limiting examples, AirplaySDK, alcheMo,Appcelerator®, Celsius, Bedrock, Flash Lite, .NET Compact Framework,Rhomobile, and WorkLight Mobile Platform. Other development environmentsmay be available without cost including, by way of non-limitingexamples, Lazarus, MobiFlex, MoSync, and Phonegap. Also, mobile devicemanufacturers distribute software developer kits including, by way ofnon-limiting examples, iPhone and iPad (iOS) SDK, Android™ SDK,BlackBerry® SDK, BREW SDK, Palm® OS SDK, Symbian SDK, webOS SDK, andWindows® Mobile SDK.

Those of skill in the art will recognize that several commercial forumsmay be available for distribution of mobile applications including, byway of non-limiting examples, Apple® App Store, Android™ Market,BlackBerry® App World, App Store for Palm devices, App Catalog forwebOS, Windows® Marketplace for Mobile, Ovi Store for Nokia® devices,Samsung® Apps, and Nintendo® DSi Shop.

Standalone Applications

A computer program may include a standalone application, which may be aprogram that may be run as an independent computer process, not anadd-on to an existing process, e.g., not a plug-in. Those of skill inthe art will recognize that standalone applications may be oftencompiled. A compiler may be a computer program(s) that transforms sourcecode written in a programming language into binary feature code such asassembly language or machine code. Suitable compiled programminglanguages include, by way of non-limiting examples, C, C++,Featureive-C, COBOL, Delphi, Eiffel, Java™, Lisp, Python™, Visual Basic,and VB .NET, or combinations thereof. Compilation may be oftenperformed, at least in part, to create an executable program. A computerprogram may include one or more executable complied applications.

Web Browser Plug-Ins

A computer program may include a web browser plug-in. In computing, aplug-in may be one or more software components that add specificfunctionality to a larger software application. Makers of softwareapplications may support plug-ins to enable third-party developers tocreate abilities which extend an application, to support easily addingnew features, and to reduce the size of an application. When supported,plug-ins may enable customizing the functionality of a softwareapplication. For example, plug-ins are commonly used in web browsers toplay video, generate interactivity, scan for viruses, and displayparticular file types. Those of skill in the art will be familiar withseveral web browser plug-ins including, Adobe® Flash® Player, Microsoft®Silverlight®, and Apple® QuickTime®. The toolbar may comprise one ormore web browser extensions, add-ins, or add-ons. The toolbar maycomprise one or more explorer bars, tool bands, or desk bands.

In view of the disclosure provided herein, those of skill in the artwill recognize that several plug-in frameworks may be available thatenable development of plug-ins in various programming languages,including, by way of non-limiting examples, C++, Delphi, Java™, PHP,Python™, and VB .NET, or combinations thereof.

Web browsers (also called Internet browsers) may be softwareapplications, designed for use with network-connected digital processingdevices, for retrieving, presenting, and traversing informationresources on the World Wide Web. Suitable web browsers include, by wayof non-limiting examples, Microsoft® Internet Explorer®, Mozilla®Firefox®, Google® Chrome, Apple® Safari®, Opera Software® Opera®, andKDE Konqueror. The web browser may be a mobile web browser. Mobile webbrowsers (also called mircrobrowsers, mini-browsers, and wirelessbrowsers) may be designed for use on mobile digital processing devicesincluding, by way of non-limiting examples, handheld computers, tabletcomputers, netbook computers, subnotebook computers, smartphones, musicplayers, personal digital assistants (PDAs), and handheld video gamesystems. Suitable mobile web browsers include, by way of non-limitingexamples, Google® Android® browser, RIM BlackBerry® Browser, Apple®Safari®, Palm® Blazer, Palm® WebOS® Browser, Mozilla® Firefox® formobile, Microsoft® Internet Explorer® Mobile, Amazon® Kindle® Basic Web,Nokia® Browser, Opera Software® Opera® Mobile, and Sony® PSP™ browser.

Software Modules (General)

The methods, software, systems, and platforms disclosed herein maycomprise one or more softwares, servers, and database modules, or use ofthe same. In view of the disclosure provided herein, software modulesmay be created by techniques known to those of skill in the art usingmachines, software, and languages known to the art. The software modulesdisclosed herein may be implemented in a multitude of ways. A softwaremodule may comprise a file, a section of code, a programming feature, aprogramming structure, or combinations thereof. A software module maycomprise a plurality of files, a plurality of sections of code, aplurality of programming features, a plurality of programmingstructures, or combinations thereof. The one or more software modulesmay comprise, by way of non-limiting examples, a web application, amobile application, and a standalone application. Software modules maybe in one computer program or application. Software modules may be inmore than one computer program or application. Software modules may behosted on one machine. Software modules may be hosted on more than onemachine. Software modules may be hosted on cloud computing platforms.Software modules may be hosted on one or more machines in one location.Software modules may be hosted on one or more machines in more than onelocation.

Databases

The methods, software, systems, and platforms disclosed herein maycomprise one or more databases, or use of the same. In view of thedisclosure provided herein, those of skill in the art will recognizethat many databases may be suitable for storage and retrieval of imaginginformation. Suitable databases may include, by way of non-limitingexamples, relational databases, non-relational databases, featureoriented databases, feature databases, entity-relationship modeldatabases, associative databases, and XML databases. A database may beinternet-based. A database may be web-based. A database may be cloudcomputing-based. A database may be based on one or more local computerstorage devices.

EXAMPLES

The following illustrative examples are representative of specificembodiments of the methods, systems, and platforms described herein, butare not meant to be limiting in any way.

Example 1 Optical Instrument

FIG. 1 shows one embodiment of the optical instrument. This embodimentwas used for simultaneously imaging 2 adjacent wells of a 16-wellmicroscope slide. Each well contained 1024 (32×32) features, also calledspots, which may be labeled with fluorescence. A spot diameter wasapproximately 80 microns. Center-to-center distance between adjacentspots was 161 microns. The purpose of the instrument was to determinethe brightness of each spot. FIG. 1E shows the translation stage system105, imaging system 106, and illumination system 107. The translationstage system contained a single-axis translation stage which wasconstructed from a Misumi model SSELBW9-170 recirculating ball slidedriven by a Haydon Kerk 26000-series linear actuator. A holder for a16-well microscope slide was mounted on the translation stage. Thelinear actuator was controlled by a Peter Norberg Consulting modelBC2D20-0700 motion controller. FIG. 1G shows a USB hub 112, customcircuit board 113, and a motion controller 114. The motion controllerand the CCD camera were USB devices. The USB hub allowed communicationbetween a computer and the instrument to take place over a single USBcable. The custom circuit board contained a Luxdrive model 3021-D-E-1000LED driver. The custom circuit board contained a logic chip tosynchronize the LED with the CCD camera (turn the LED on when the CCDcamera starts an exposure and off when the CCD camera finishes anexposure) and to prevent the LED from turning on when the instrument'sdoor is open.

Example 2 Imaging System

An embodiment of an imaging system is illustrated in FIG. 2. Lightemitted by dye molecules on a surface of the support 205 was collimatedby an achromatic cemented doublet lens 204, filtered by a bandpassfilter 203, and focused by a camera lens 202 onto the sensor 201 of aCCD camera. Lens 204 (Edmund Optics model 47640) had a focal length of85 mm and a diameter of 25 mm. Filter 203 (Semrock model FF01-593/40-25)was an emission bandpass filter for use with cy3 or phycoerythrin dye.Lens 202 (Fujinon model HF25HA-1B) has a focal length of 25 mm. Lens 202was a multi-element lens, but it is shown in FIG. 2 as aninfinitesimally thin single-element lens because the design details ofthe multi-element lens were proprietary to Fujinon. The adjustableaperture stop of lens 202 was set to 2.8. The CCD camera (Point GreyResearch model CMLN-13S2M-CS) had 1296×964 pixels and a pixel size of3.75 microns. In this embodiment only the central 1280×640 pixels wereused. The camera's plastic housing was removed and the camera's circuitboard was cooled by a small fan. Lenses 204 and 202 formed afinite-conjugate imaging system with a magnification of 0.3.

Example 3 Illumination System

An embodiment of an illumination system is illustrated in FIG. 3. Lightemitted by light source 301 was collimated by lens 302 and then passedthrough aperture 303, bandpass filter 304, and lenses 305, 306, and 307,before reaching sample 308. Light source 301 (LedEngin model LZ4-40G100)was an LED with a peak emission wavelength of approximately 525 nm. Lens302 (Thorlabs model ACL2520-A) was an aspheric lens with a diameter of25 mm and a focal length of 20 mm. Aperture 303 (Fotofab custom part)was a rectangular hole (19 mm×7.5 mm) in a 25-mm-diameter steel disk.Filter 304 (Semrock model FF01-531/40-25) was an excitation bandpassfilter for use with cy3 or phycoerythrin dye. Lenses 305, 306, and 307were plano-convex lenses with diameters of 25 mm and focal lengths of 60mm. Lenses 301 and 302 formed a finite-conjugate imaging system with amagnification of 3 and imaged light source 301 onto the pupils of lenses306 and 307. Lenses 306 and 307 formed a finite-conjugate imaging systemwith a magnification of 1 and imaged aperture 303 onto sample 308. Theillumination system was tilted at 45 degrees with respect to sample 308.The illuminated area was approximately 19 mm×10.6 mm, where 10.6 mm(=7.5 mm/cosine (45 degrees)).

Example 4 Reference Probe Preparation

The purpose of this experiment was to illustrate the use of an ad hocmethod to count the number of hybridizations taking place on an array.This example used probes that the specific DNA sequences attached to anarray. The 32×32 feature arrays used in this experiment contain 960different measure spots along with 32 positive control probes and 32negative control probes (see FIGS. 15 and 16). The 32 positive controlprobes were used to ensure actual binding can occur by using stockoligonucleotide, while the 32 negative control probes contained emptyspots with no probes at all. In the image analysis step, we considered aprobe to have intensity above the set intensity threshold, then wereferred to the probe as a positive probe, while if the probe intensitywas below the set intensity threshold, we referred to the probe as anegative feature. Positive probes were assumed to measure whether therewas a significant amount of corresponding complementary oligonucleotidein the sample, while negative features represented absentoligonucleotides. The positive probes were otherwise referred to aslabels, meaning we can count up to 960 unique labels or barcodes, tomeasure 960 copies of oligonucleotides in the sample, which can then befurther generalized to predict the actual amount of oligonucleotides inthe original sample. Depending on the experiment, out of the M totallabels, or 960 total labels, we could calculate the total number ofcopies, N, of the oligonucleotides in the sample, by predicting N fromthe actual observed unique barcodes or number of positive probes, k.

Example 5 Threshold Computation

The purpose of this experiment was to demonstrate one method to computea threshold for discriminating between labeled and non-labeled featureson an array.

-   -   I. Set I_(LL), intensity lower limit, I_(UL), intensity upper        limit, and w, window size.    -   II. Obtain a set of feasible threshold intensities,        y={y_(i):I_(LL)<I_(i)<I_(UL)}    -   III. Sort y in increasing order to obtain y*.    -   IV. Calculate d={d₁, d₂, d_(i), . . . , d_(m)}, where        d_(i)=y_(i+1)*−y_(i)*.    -   V. Calculate a gap statistic for each of the observed        intensities:

$x_{j} = \frac{\sum\limits_{i = {j - w}}^{j + w}d_{i}}{{2\; w} + 1}$

-   -   VI. Identify the threshold c, such that c=max(x_(j))    -   VII. Count the number of spots, k, above the threshold c, where        k=Σ_(i=1) ^(m)I[y_(i)>c].    -   VIII. Given a number of simulations desired, nsim, perform the        following procedure nsim times: Randomly select m values with        replacement from y={y₁, y₂, . . . , y_(m)} to obtain y_(sim).        Then repeat Step I-VII with y_(sim) to obtain a final count.    -   IX. Calculate {circumflex over (σ)}_(k) the standard deviation        of the nsim simulated counts.    -   X. Calculate the 95% CI for the count as:

[k−1.96{circumflex over (σ)}_(k) ,k+1.96{circumflex over (σ)}_(k)].

-   -   Note that in order to obtain the true estimate of the molecule        count in the sample, we needed to transform by:

$N = {{- m}*{\log \left( {1 - \frac{k}{m}} \right)}}$

-   -   and similarly, for the 95% CI upper and lower values, where m is        the total number of features on the array.

Example 6 Detection of Kan Genes

The purpose of this experiment was to determine the count of kan genesin a sample. The sample containing the kan genes was hybridized to anarray. FIG. 4A displays a region of the array acquired from the imagingsystem. The bright intensity at a spot was correlated with a higherprobability of a gene being present at the spot. The image analysissoftware examined the statistics of the intensity distribution, such asdeviance, skewness, kurtosis, and median. These statistics providedguidance for the software to automatically choose the best method todetect the presence of kan genes. In this example, a mixture modelalgorithm was used to determine the intensity threshold to be 6.6, whichoptimally divided the intensity distribution into “on” and “off”domains, as shown in FIG. 4B.

Example 7 Titration Experiment

The purpose of this experiment was to detect the presence of molecularhybridization in a titration experiment. After obtaining the intensitymeasurements of a region, the intensity distribution was computed and isshown in FIG. 5. A person with ordinary skill can identify two modes inthe distribution; however, it was very difficult to determine theprecise value of the threshold. The invented software automated the taskof determining the signal intensity threshold, and determined that anintensity value of 6.02 provides the optimal threshold fordistinguishing between labeled and non-labeled features.

Example 8 Background Adjustment

The purpose of this experiment was to demonstrate use of one backgroundsubtraction method to process images. FIG. 6A shows an acquired imagewith pronounced artifacts. A systematic background subtraction wasperformed to reduce noise. We defined an analysis window centered on aspot. The software then calculated the mean spot intensity, S, spotstandard deviation σ_(S), number of spot pixels n_(S), background meanB, background standard deviation σ_(B), and number of background pixelsn_(B). Then, the software calculated the log 2 background subtractedintensity statistic for each spot:

$I = \frac{{\log_{2}\left( {16\; \overset{\_}{S}} \right)} - {\log_{2}\left( {16\; \overset{\_}{B}} \right)}}{\sqrt{\frac{\tau_{S}^{2}}{n_{S}} + \frac{\tau_{B}^{2}}{n_{B}}}}$where$\tau_{S} = {{\log_{2}\left( {16\left( {\sigma_{S} + \overset{\_}{S}} \right)} \right)} - {\log_{2}\left( {16\; \sigma_{S}} \right)}}$$\tau_{B} = {{\log_{2}\left( {16\left( {\sigma_{B} + \overset{\_}{B}} \right)} \right)} - {\log_{2}\left( {16\; \sigma_{B}} \right)}}$

FIGS. 6B and 6C show the intensity distributions before and afterbackground adjustment, respectively, demonstrating that backgroundcorrection enhances the ability of the software to correctly evaluatethe presence of the labeled features on the array.

Example 9 Alternative Background Correction

The purpose of this experiment was an alternative way to adjustbackground. We defined an analysis window centered on a spot. Thesoftware then calculated the median spot intensity {tilde over (S)} andmedian local background intensity {tilde over (B)}. Then, the softwarecalculated the log 2 background subtracted intensity statistic for eachspot:

l=log₂(16{tilde over (S)})−log₂(16{tilde over (S)}).

Example 10 Pixel 16 Cartridge and Custom Microarray

This example illustrated one embodiment of an array for use with thedisclosed methods, systems, and platforms in performing stochasticlabeling experiment.

The Pixel 16 cartridge consists of (i) an epoxysilane functionalizedglass slide serving as an array substrate, (ii) 16 copies of the custommicroarray described in FIGS. 14-16, printed on the functionalizedsurface of the slide, and (iii) a polymer well frame affixed to theprinted side of the slide which serves to define 16 wells which arefluidically separate and in register with the array pattern. The wellframe is affixed to the slide following array printing using a die-cutdouble-sided adhesive.

Custom DNA microarray layout. The microarray pattern consists of a 32×32array of spots as shown in FIGS. 15 and 16. Fiducial spots in the topand bottom rows permit location of the array in the scanned images.Also, the fiducial spots are arranged in an asymmetric pattern whoseorientation is readily identifiable: the top row has a distinctivepattern whose ends are distinct, and the bottom row is different fromthe top row. This permits easy manual and automatic identification ofincorrect placement of the Pixel 16, and also facilitates detection ofimaging problems. The remaining 960 spots are each associated with oneof the unique probe sequences listed in Table 1.

Oligonucleotide sequences and solution components. Oligonucleotidesolutions are provided for preparation of printing solutions in 96-wellmicroplates. Concentration as supplied is 100 μM in H2O. Dilution priorto printing is performed using the Tecan GenMate. Dilution is 880 μL ofstock oligo+1320 μL of buffer. The dilution buffer used is 250 mM sodiumphosphate with 0.00833% sarcosyl. Buffer is filtered using a 0.2 μmfilter. Three sets of plates are prepared in each probe preparationoperation. Tips are discarded after each source plate. The finaldispensed solution is 40 μM DNA in 150 mM sodium phosphate with 0.005%sarcosyl. The fiducial oligo is supplied at 500 μM in H2O. The fiducialoligonucleotide sequence is: 5′-/5AmMC6/TCC TGA ACG GTA GCATCT TGA CGAC-3′ (SEQ ID NO: 1), 25 bases, 5′ Amino Modifier C6, standard desalting;supplied at 500 μM in H₂O. The fiducial is diluted by mixing 176 μL offiducial, 704 μL of water, and 1320 μL of buffer. The final fiducialmixture is 40 μM in 150 mM sodium phosphate with 0.005% sarcosyl.

Table of oligonucleotide sequences. The oligonucleotide sequences forthe 960 probe sequences (i.e. the sequences that are complementary tothe set of stochastic labeling sequences used in molecular countingexperiments) are listed in Table 1.

TABLE 1 Oligonucleotide Probe Sequences for Custom Microarray(Table 1 discloses SEQ ID NOS 2-961, respectively, in order of appearance)Calc'd Plate IDT Well Seq IDT Mfg Molec. Name Ref. # Pos. Name SequenceID Weight T_(m) AJ_P1 85652789 A01 AJ_1 /5AmMC6/CCC AAA GGG TAC CAG106534039 8795 61.7 AGC TTA AGG TCA A AJ_P1 85652790 A02 AJ_2/5AmMC6/CCC AAA GCG TTA AGG 106534040 8727 59.7 TTT CTT GTC ACA A AJ_P185652791 A03 AJ_3 /5AmMC6/CCC AAG TCG TAC GAA 106534041 8675 61.8CTC ACC ACA TGA A AJ_P1 85652792 A04 AJ_4/5AmMC6/CCC AAA CTT GTT CCC TTG 106534042 8672 60.3 AGA CCA GTA A AJ_P185652793 A05 AJ_5 /5AmMC6/CCC AAG ACT TCT ACC 106534043 8657 60.7CTA GGT TCC AGA A AJ_P1 85652794 A06 AJ_6 /5AmMC6/CCC AAC CAG ACT TGG106534044 8755 62.3 GTA CGT GAA ACA A AJ_P1 85652795 A07 AJ_7/5AmMC6/CCC AAC GAC TGG TTC 106534045 8786 62.3 TGA AGT GGA ACA A AJ_P185652796 A08 AJ_8 /5AmMC6/CCC AAT TTA GCT TCG 106534046 8712 60.4TGA GTC AGA CCA A AJ_P1 85652797 A09 AJ_9 /5AmMC6/CCC AAC TCG AAG AGT106534047 8752 59.8 GGT CAG TCT TTA A AJ_P1 85652798 A10 AJ_10/5AmMC6/CCC AAT CGC AAG GAG 106534048 8745 58.4 ACA TAG TCT TTA A AJ_P185652799 A11 AJ_11 /5AmMC6/CCC AAG TCC TAG TGA 106534049 8761 60GAG CAA CGT TTA A AJ_P1 85652800 A12 AJ_12 /5AmMC6/CCC AAG GAA CCT ACT106534050 8697 61.4 GTC CTT GTC AGA A AJ_P1 85652801 B01 AJ_13/5AmMC6/CCC AAA CTA GAA GAC 106534051 8779 59.7 GAG TTC GAG TCA A AJ_P185652802 B02 AJ_14 /5AmMC6/CCC AAG GAC ATA CTC 106534052 8699 60AAC GTA GCT CAA A AJ_P1 85652803 B03 AJ_15 /5AmMC6/CCC AAG GCA TTT GCA106534053 8690 61.9 ACC TCA CAT GAA A AJ_P1 85652804 B04 AJ_16/5AmMC6/CCC AAG TAC CCA TCC 106534054 8666 61.3 ACT GTC GAG TAA A AJ_P185652805 B05 AJ_17 /5AmMC6/CCC AAA GCG TTT GTG 106534055 8745 59.4TAA CAG ACC ATA A AJ_P1 85652806 B06 AJ_18 /5AmMC6/CCC AAA TGG TCT GGT106534056 8737 62.3 TCG ACA GTC ACA A AJ_P1 85652807 B07 AJ_19/5AmMC6/CCC AAG AGG TAC AAC 106534057 8795 60.6 GAC TCT AGG GTA A AJ_P185652808 B08 AJ_20 /5AmMC6/CCC AAG AAC TTC TAC 106534058 8687 58.9TTG CTT CGT GAA A AJ_P1 85652809 B09 AJ_21 /5AmMC6/CCC AAG CAC TTT CTG106534059 8687 58.8 TTA ACT AGC TGA A AJ_P1 85652810 B10 AJ_22/5AmMC6/CCC AAG AAC CTC TCT 106534060 8672 58.6 CTA GTG CTA GTA A AJ_P185652811 B11 AJ_23 /5AmMC6/CCC AAG CCT TTA AGC 106534061 8681 60.4CTA AAG TCC TGA A AJ_P1 85652812 B12 AJ_24 /5AmMC6/CCC AAT CTG GTA GCT106534062 8672 60.3 CAA CAT CCT TGA A AJ_P1 85652813 C01 AJ_25/5AmMC6/CCC AAA GGA CTC CAT 106534063 8795 61.8 GGA GAA GTG TCA A AJ_P185652814 C02 AJ_26 /5AmMC6/CCC AAG AAC CCT TTC 106534064 8657 62.4TGG AAG CTT CCA A AJ_P1 85652815 C03 AJ_27 /5AmMC6/CCC AAA TTC GCT TCC106534065 8712 60.1 TAG TAG TGG ACA A AJ_P1 85652816 C04 AJ_28/5AmMC6/CCC AAC CGT ACG AAG 106534066 8681 59.4 ACC TAG TTT CTA A AJ_P185652817 C05 AJ_29 /5AmMC6/CCC AAT CAC GAA GAG 106534067 8745 58.4AGT CAC TGT TTA A AJ_P1 85652818 C06 AJ_30 /5AmMC6/CCC AAG AAA CAT AAA106534068 8763 59.3 CTC GAG TTG CGA A AJ_P1 85652819 C07 AJ_31/5AmMC6/CCC AAC CAG TTA CGT 106534069 8752 60.7 GAG TGT TGC TAA A AJ_P185652820 C08 AJ_32 /5AmMC6/CCC AAA CTC GTG ACT 106534070 8672 60.5CCT GTT TCA GAA A AJ_P1 85652821 C09 AJ_33 /5AmMC6/CCC AAC GGT TGA AGA106534071 8779 60.6 GAC TCC TGA AAA A AJ_P1 85652822 C10 AJ_34/5AmMC6/CCC AAA TTG CTC TGG 106534072 8705 59.8 TCA CAT CGA AAA A AJ_P185652823 C11 AJ_35 /5AmMC6/CCC AAC AGG ACT TGT 106534073 8752 60.7GCT ACG TGT TAA A AJ_P1 85652824 C12 AJ_36 /5AmMC6/CCC AAA TTT CGT GTG106534074 8672 61.9 TCA ACC ATG CCA A AJ_P1 85652825 D01 AJ_37/5AmMC6/CCC AAC GTG AAG GCT 106534075 8754 59.7 TAA CAA CAT TGA A AJ_P185652826 D02 AJ_38 /5AmMC6/CCC AAT GAA CAC AAC 106534076 8723 59TAC GAA GCT GTA A AJ_P1 85652827 D03 AJ_39 /5AmMC6/CCC AAA CTT CCG TTG106534077 8687 58.7 TTA CTA GTC GAA A AJ_P1 85652828 D04 AJ_40/5AmMC6/CCC AAG GAG TAC AAG 106534078 8786 61 CTT CCT AGG GTA A AJ_P185652829 D05 AJ_41 /5AmMC6/CCC AAG TGC TAA ACT 106534079 8687 58.8GCT CTT TAC GTA A AJ_P1 85652830 D06 AJ_42 /5AmMC6/CCC AAA GAA ACT GCA106534080 8705 59.5 TCT CCT TTG GAA A AJ_P1 85652831 D07 AJ_43/5AmMC6/CCC AAG GAC TAA GTT 106534081 8666 61.4 CCA CTC ACC TGA A AJ_P185652832 D08 AJ_44 /5AmMC6/CCC AAA GTT GTC TGG 106534082 8752 60.5TTC ACT CGA GAA A AJ_P1 85652833 D09 AJ_45 /5AmMC6/CCC AAC GTT CTA AGT106534083 8727 59.2 TTG CTT CGA AGA A AJ_P1 85652834 D10 AJ_46/5AmMC6/CCC AAC TAA AGG TTG 106534084 8730 61.5 TGC ATC CAA GCA A AJ_P185652835 D11 AJ_47 /5AmMC6/CCC AAA GGC TTC ACG 106534085 8696 59.4ACA TGT CAT TTA A AJ_P1 85652836 D12 AJ_48 /5AmMC6/CCC AAC TGC TAG GTT106534086 8681 59.7 CCT ACA CAA GTA A AJ_P1 85652837 E01 AJ_49/5AmMC6/CCC AAA TCA GTA GCT 106534087 8699 59.8 ACA CCA CAG GTA A AJ_P185652838 E02 AJ_50 /5AmMC6/CCC AAG ACT GCA AGC 106534088 8690 60.6TCA CTA CAT TGA A AJ_P1 85652839 E03 AJ_51 /5AmMC6/CCC AAG CTA CTC CTC106534089 8690 58.9 TAA GAG CAT AGA A AJ_P1 85652840 E04 AJ_52/5AmMC6/CCC AAT GGA ACG CTA 106534090 8779 60.9 AGG TGT AAA CCA A AJ_P185652841 E05 AJ_53 /5AmMC6/CCC AAG AAA CTA ACC 106534091 8690 61.5TTG GCT TGC CAA A AJ_P1 85652842 E06 AJ_54 /5AmMC6/CCC AAC CAT TAG ACC106534092 8672 61.3 TTG TGT TGC CAA A AJ_P1 85652843 E07 AJ_55/5AmMC6/CCC AAG GTC TGA CAG 106534093 8777 61.7 TAG GTG TTC CAA A AJ_P185652844 E08 AJ_56 /5AmMC6/CCC AAT TTC GCA AGC 106534094 8696 59.7CTT GGT ACA TAA A AJ_P1 85652845 E09 AJ_57 /5AmMC6/CCC AAG TTT CTA GCC106534095 8657 61.2 TAC CAC TAC GGA A AJ_P1 85652846 E10 AJ_58/5AmMC6/CCC AAA TAG ACC TAA 106534096 8779 60.1 CGG AAG CTG TGA A AJ_P185652847 E11 AJ_59 /5AmMC6/CCC AAG GAG TCA TCC 106534097 8712 60.7ATG CAT CTT TGA A AJ_P1 85652848 E12 AJ_60 /5AmMC6/CCC AAC CGT ACT AGC106534098 8721 60.5 TTG GGT TAA ACA A AJ_P1 85652849 F01 AJ_61/5AmMC6/CCC AAA AAG GCT AGC 106534099 8696 59 CTT CTG ACT TTA A AJ_P185652850 F02 AJ_62 /5AmMC6/CCC AAA GAG CTC TGC 106534100 8705 58.8ACT ACA AGT TTA A AJ_P1 85652851 F03 AJ_63 /5AmMC6/CCC AAC AGC TAA CGG106534101 8779 60 TAG TAA AGG TCA A AJ_P1 85652852 F04 AJ_64/5AmMC6/CCC AAA GCT TTC CGT TTC 106534102 8696 60 AAA GTG ACA A AJ_P185652853 F05 AJ_65 /5AmMC6/CCC AAG TCC ATG CTT 106534103 8690 61.3CCA GTG ACA AAA A AJ_P1 85652854 F06 AJ_66 /5AmMC6/CCC AAG TAG CTT TGC106534104 8687 58.4 TCT ACT CGT AAA A AJ_P1 85652855 F07 AJ_67/5AmMC6/CCC AAC TTC GAA CTA 106534105 8779 59.7 AGG AGT AGA GCA A AJ_P185652856 F08 AJ_68 /5AmMC6/CCC AAT TCA GTC CTA 106534106 8770 58.5GAG GAG AGA CTA A AJ_P1 85652857 F09 AJ_69 /5AmMC6/CCC AAT AGG TCT GTC106534107 8672 59.6 TTA CCC AAC GTA A AJ_P1 85652858 F10 AJ_70/5AmMC6/CCC AAC GTG AGG AAA 106534108 8770 60.7 GTT CTG CTA ACA A AJ_P185652859 F11 AJ_71 /5AmMC6/CCC AAG TTG GCA ACT 106534109 8712 60.7TGC TCT CTA AGA A AJ_P1 85652860 F12 AJ_72 /5AmMC6/CCC AAG ACA TCT CTC106534110 8690 59 TCA GAG CTA GAA A AJ_P1 85652861 G01 AJ_73/5AmMC6/CCC AAT TTC GCA TGT CTC 106534111 8672 60.9 ATC AGG ACA A AJ_P185652862 G02 AJ_74 /5AmMC6/CCC AAA GCC TTC CTT 106534112 8721 60.6GGT ACT GAA AGA A AJ_P1 85652863 G03 AJ_75 /5AmMC6/CCC AAA CTT GCC TTG106534113 8696 59.9 CGT ACT GTA AAA A AJ_P1 85652864 G04 AJ_76/5AmMC6/CCC AAC ACT TTG TAC 106534114 8761 59.7 GGT AGA GAC GTA A AJ_P185652865 G05 AJ_77 /5AmMC6/CCC AAG TTT CCA TCA 106534115 8681 61.2ACC GAA GCT TGA A AJ_P1 85652866 G06 AJ_78 /5AmMC6/CCC AAG CAT TAC CAA106534116 8699 61 ACT GGA ACC TGA A AJ_P1 85652867 G07 AJ_79/5AmMC6/CCC AAC CGT ACA ACT 106534117 8687 59.7 TGT TCG TTT GAA A AJ_P185652868 G08 AJ_80 /5AmMC6/CCC AAC AGC TAG TAG 106534118 8690 60.7CAC ACC ATT TGA A AJ_P1 85652869 G09 AJ_81 /5AmMC6/CCC AAC CTC ACG AAA106534119 8690 61.2 GCA TCA TTG TGA A AJ_P1 85652870 G10 AJ_82/5AmMC6/CCC AAA CAA AGT GAG 106534120 8739 60.5 GTC ATC TCG ACA A AJ_P185652871 G11 AJ_83 /5AmMC6/CCC AAG AAA CCT TCT 106534121 8721 59.9TGT AGG ACT CGA A AJ_P1 85652872 G12 AJ_84 /5AmMC6/CCC AAA AGC CTA AGC106534122 8696 58.9 TCT GTC AGT TTA A AJ_P1 85652873 H01 AJ_85/5AmMC6/CCC AAA CGT TCC CTT 106534123 8681 60.9 CAT GTC GAA AGA A AJ_P185652874 H02 AJ_86 /5AmMC6/CCC AAG TAG CAC TGA 106534124 8699 60.7CAC CAA GCA TTA A AJ_P1 85652875 H03 AJ_87 /5AmMC6/CCC AAG TTT GAC TCC106534125 8657 62.2 AAG CCT ACG TCA A AJ_P1 85652876 H04 AJ_88/5AmMC6/CCC AAA CCG TTG GTG 106534126 8770 61.2 AAG CCT TAA AGA A AJ_P185652877 H05 AJ_89 /5AmMC6/CCC AAG CCT ACA CCT 106534127 8675 61.9TCA GTG AAC AGA A AJ_P1 85652878 H06 AJ_90 /5AmMC6/CCC AAC AGC TCA AGC106534128 8723 59.2 AGT TAG TAA ACA A AJ_P1 85652879 H07 AJ_91/5AmMC6/CCC AAT ACG CAA GCA 106534129 8745 59.3 TGT AGG TTT ACA A AJ_P185652880 H08 AJ_92 /5AmMC6/CCC AAC ACG AGT CGT 106534130 8727 59.3TAG TTG TTT CAA A AJ_P1 85652881 H09 AJ_93 /5AmMC6/CCC AAT TCG GAA GAC106534131 8690 59.6 CTA CTA ACC TGA A AJ_P1 85652882 H10 AJ_94/5AmMC6/CCC AAA GGT CTC TAC 106534132 8763 58.2 GAA AGG AAC ATA A AJ_P185652883 H11 AJ_95 /5AmMC6/CCC AAG TGC TAG ACG 106534133 8761 60.6TCT GTG TCA AAA A AJ_P1 85652884 H12 AJ_96 /5AmMC6/CCC AAA CCA GTG GAC106534134 8657 61 TTC TCT CCT AGA A AJ_P2 85652886 A01 AJ_97/5AmMC6/CCC AAC ATG TAG GAG 106534135 8746 61.3 ACG TAG TTC CCA A AJ_P285652887 A02 AJ_98 /5AmMC6/CCC AAG AAC TCT CTG 106534136 8752 60.2GTT AGG CTT GAA A AJ_P2 85652888 A03 AJ_99 /5AmMC6/CCC AAG GAC ATC CAC106534137 8675 62.1 ATC GTC TGA CAA A AJ_P2 85652889 A04 AJ_100/5AmMC6/CCC AAA CTT GTT GGG 106534138 8736 59.8 TTC AGC TAA CAA A AJ_P285652890 A05 AJ_101 /5AmMC6/CCC AAC ACG TGT CCT 106534139 8681 61.2GTC ATG TCA AAA A AJ_P2 85652891 A06 AJ_102 /5AmMC6/CCC AAT CGG AAA CCA106534140 8705 59.4 ACG TTA GCT TTA A AJ_P2 85652892 A07 AJ_103/5AmMC6/CCC AAG GAC TTA GGT 106534141 8777 61.4 ACC TGT TCG GAA A AJ_P285652893 A08 AJ_104 /5AmMC6/CCC AAG ACT TAA CAA 106534142 8739 60.1CCT GTG ACG AGA A AJ_P2 85652894 A09 AJ_105 /5AmMC6/CCC AAG TTA ACA TGC106534143 8779 60.7 AGA CGA ACG GTA A AJ_P2 85652895 A10 AJ_106/5AmMC6/CCC AAG CGT ACA ACT 106534144 8687 58.9 CTT GTC AGT TTA A AJ_P285652896 A11 AJ_107 /5AmMC6/CCC AAG TAA CAC CTT 106534145 8746 61.9CTG AGC AGT GGA A AJ_P2 85652897 A12 AJ_108 /5AmMC6/CCC AAG ACC TAC CTC106534146 8675 60.7 TCA GGA ACA GTA A AJ_P2 85652898 B01 AJ_109/5AmMC6/CCC AAA CCT GAC CTT 106534147 8739 59.9 AGG AAG AGC ATA A AJ_P285652899 B02 AJ_110 /5AmMC6/CCC AAC AAA GTT TGT 106534148 8736 59.3CTC AGT TAG CGA A AJ_P2 85652900 B03 AJ_111 /5AmMC6/CCC AAC GGT AGC ATT106534149 8752 60.5 GTT CCT GTA GAA A AJ_P2 85652901 B04 AJ_112/5AmMC6/CCC AAC TAG GTT TGT TCT 106534150 8727 58 AGA CAG CTA A AJ_P285652902 B05 AJ_113 /5AmMC6/CCC AAG TCT CTA CGT 106534151 8681 59.8TCC ATC GAA AGA A AJ_P2 85652903 B06 AJ_114/5AmMC6/CCC AAA CCT TCG TTC TTG 106534152 8672 60.7 AGT ACA GCA A AJ_P285652904 B07 AJ_115 /5AmMC6/CCC AAG AAC ACT CCT 106534153 8666 62.2CAT GTG ACT GCA A AJ_P2 85652905 B08 AJ_116 /5AmMC6/CCC AAA CGC TTG GTA106534154 8763 59.3 ACA AAG ACA GTA A AJ_P2 85652906 B09 AJ_117/5AmMC6/CCC AAC CCT AGA GTA 106534155 8721 58.4 GTA CTA CGG TTA A AJ_P285652907 B10 AJ_118 /5AmMC6/CCC AAC CTG AGG TAG 106534156 8779 60.3TGA CTG AAA CAA A AJ_P2 85652908 B11 AJ_119 /5AmMC6/CCC AAG CTA CGA ACT106534157 8727 59.7 TGG TTG TTT CAA A AJ_P2 85652909 B12 AJ_120/5AmMC6/CCC AAG CAA GTC CTA 106534158 8752 60.8 GGT TGT GTT CAA A AJ_P285652910 C01 AJ_121 /5AmMC6/CCC AAC TCC ATG TCA 106534159 8755 61.9AGG AAG GGT ACA A AJ_P2 85652911 C02 AJ_122 /5AmMC6/CCC AAT CCG AAC ACG106534160 8723 58.7 AAG TAC AAG TTA A AJ_P2 85652912 C03 AJ_123/5AmMC6/CCC AAC ACG TTG ACA 106534161 8727 60.1 TTG TTG GCT TAA A AJ_P285652913 C04 AJ_124 /5AmMC6/CCC AAC CTC TAG GAA 106534162 8675 60.9CGT AGT ACA CCA A AJ_P2 85652914 C05 AJ_125 /5AmMC6/CCC AAT AGG ACA CCA106534163 8699 60.3 CAG TTC ATC GAA A AJ_P2 85652915 C06 AJ_126/5AmMC6/CCC AAA TGT CGT TCG 106534164 8736 59.7 GTT AGC TCA AAA A AJ_P285652916 C07 AJ_127 /5AmMC6/CCC AAA TCG GTT GTG 106534165 8736 59.4TCT AGC TCA AAA A AJ_P2 85652917 C08 AJ_128 /5AmMC6/CCC AAT AAG AAC GAA106534166 8723 59.3 ACG TAC CTT GCA A AJ_P2 85652918 C09 AJ_129/5AmMC6/CCC AAT CGC AAG AAC 106534167 8723 59.7 CGT TAG TCA AAA A AJ_P285652919 C10 AJ_130 /5AmMC6/CCC AAG TCA CAC GTC 106534168 8657 61.9TCC ACA GGT TTA A AJ_P2 85652920 C11 AJ_131 /5AmMC6/CCC AAG AGC TTA CAT106534169 8752 59.4 CGT TCT AGG GTA A AJ_P2 85652921 C12 AJ_132/5AmMC6/CCC AAG ACC TTC TCC 106534170 8697 61 TTG ACA GAG GTA A AJ_P285652922 D01 AJ_133 /5AmMC6/CCC AAA AGG CTT AGC 106534171 8687 58.6TCT CTT TAC TGA A AJ_P2 85652923 D02 AJ_134 /5AmMC6/CCC AAG TCG TAA CAG106534172 8755 61.9 AGG TGT CCA CAA A AJ_P2 85652924 D03 AJ_135/5AmMC6/CCC AAA CTA CTG CAA 106534173 8761 60.5 GTG GTA GGT TCA A AJ_P285652925 D04 AJ_136 /5AmMC6/CCC AAT TTC GGA ACC 106534174 8746 62.3AGT ACC ATG GGA A AJ_P2 85652926 D05 AJ_137 /5AmMC6/CCC AAT CGA GAA GCA106534175 8705 59.1 ACT TCC TTG TAA A AJ_P2 85652927 D06 AJ_138/5AmMC6/CCC AAT GGA GAC TTC 106534176 8752 60.3 CGT ACT GTT GAA A AJ_P285652928 D07 AJ_139 /5AmMC6/CCC AAA CAT GCG TTT 106534177 8687 59.6CGT AGT CTT CAA A AJ_P2 85652929 D08 AJ_140 /5AmMC6/CCC AAG AAC CTC AGC106534178 8690 60.4 TCT TTC GAA AGA A AJ_P2 85652930 D09 AJ_141/5AmMC6/CCC AAG TCC TTA AGC 106534179 8752 59.7 TGT TCG AGA GTA A AJ_P285652931 D10 AJ_142 /5AmMC6/CCC AAT CTC GAA ACT 106534180 8672 60.5CTT GTG TGA CCA A AJ_P2 85652932 D11 AJ_143 /5AmMC6/CCC AAC CAT TAG AGG106534181 8763 57.7 AAC TAA GAG CTA A AJ_P2 85652933 D12 AJ_144/5AmMC6/CCC AAC CCT AGA GTG 106534182 8755 60.7 AGT CAG GAA CTA A AJ_P285652934 E01 AJ_145 /5AmMC6/CCC AAT GAA CCA TAA 106534183 8763 59.1GAG CAA CGG TTA A AJ_P2 85652935 E02 AJ_146 /5AmMC6/CCC AAG AAC CTT CCC106534184 8672 60.3 TTA GTC GTT GAA A AJ_P2 85652936 E03 AJ_147/5AmMC6/CCC AAG TGG TCA GTA 106534185 8697 62.1 ACC CTT TCC GAA A AJ_P285652937 E04 AJ_148 /5AmMC6/CCC AAA GCA TGT ACG 106534186 8681 59.3TCT CCT ACT AGA A AJ_P2 85652938 E05 AJ_149 /5AmMC6/CCC AAG GAC TTC ACC106534187 8666 61.9 TAC GTT CGA ACA A AJ_P2 85652939 E06 AJ_150/5AmMC6/CCC AAC GAA CTT TAC 106534188 8672 60.7 CTT GTC CAT GGA A AJ_P285652940 E07 AJ_151 /5AmMC6/CCC AAC AGG TTC TTA 106534189 8690 61.1CGC AAC ACA TGA A AJ_P2 85652941 E08 AJ_152 /5AmMC6/CCC AAC TTG TTA GGG106534190 8752 60.1 TAG CTG ACT CAA A AJ_P2 85652942 E09 AJ_153/5AmMC6/CCC AAC TGG AGA AGA 106534191 8770 59.2 GAC TAC CTG TTA A AJ_P285652943 E10 AJ_154 /5AmMC6/CCC AAC TAA GGT TTG 106534192 8752 60.3GTC AGT CCT GAA A AJ_P2 85652944 E11 AJ_155 /5AmMC6/CCC AAG CAC ACT AGC106534193 8690 60.7 CTT TCT GAA AGA A AJ_P2 85652945 E12 AJ_156/5AmMC6/CCC AAG TCC TGA CGA 106534194 8777 61.6 GAG TTT GGT ACA A AJ_P285652946 F01 AJ_157 /5AmMC6/CCC AAT CCC AAG AGT 106534195 8697 61.8CTC TGG TTG ACA A AJ_P2 85652947 F02 AJ_158 /5AmMC6/CCC AAG GCA TTC AGC106534196 8687 59.8 ATT CAT TCT TGA A AJ_P2 85652948 F03 AJ_159/5AmMC6/CCC AAG TTT GAC TAC 106534197 8690 61.3 CAA GCA ACT GCA A AJ_P285652949 F04 AJ_160 /5AmMC6/CCC AAC CTT AAG CTA 106534198 8770 60AGT GTG AGA CGA A AJ_P2 85652950 F05 AJ_161 /5AmMC6/CCC AAC TTA CAG CTA106534199 8736 59.2 GTT TGA AGT GCA A AJ_P2 85652951 F06 AJ_162/5AmMC6/CCC AAC TAG TCT CTT 106534200 8727 58.3 AGA GTT TGG CAA A AJ_P285652952 F07 AJ_163 /5AmMC6/CCC AAT AAA GCT CTA 106534201 8763 58GGA GAA CAC GTA A AJ_P2 85652953 F08 AJ_164 /5AmMC6/CCC AAA GCG TAG TAG106534202 8779 59.8 TGA CTA ACG ACA A AJ_P2 85652954 F09 AJ_165/5AmMC6/CCC AAG ACG TAA ACG 106534203 8681 59.9 CTT CCT TCT AGA A AJ_P285652955 F10 AJ_166 /5AmMC6/CCC AAA GCT GTA GTA 106534204 8672 59.5CCC TTT CCT AGA A AJ_P2 85652956 F11 AJ_167 /5AmMC6/CCC AAC TCG TAC AGC106534205 8699 59.3 ATA CCT AGA AGA A AJ_P2 85652957 F12 AJ_168/5AmMC6/CCC AAT CGC TAC ATA 106534206 8723 58.9 GCA ACT GAA AGA A AJ_P285652958 G01 AJ_169 /5AmMC6/CCC AAC TTG GCA ACG 106534207 8761 61TGT GTA GTA CAA A AJ_P2 85652959 G02 AJ_170 /5AmMC6/CCC AAA CCT GTT ACG106534208 8696 59.9 CTT GTG CTA AAA A AJ_P2 85652960 G03 AJ_171/5AmMC6/CCC AAA GCT TGG TTG 106534209 8727 59.4 TAA CTT TAC CGA A AJ_P285652961 G04 AJ_172 /5AmMC6/CCC AAG AGA CCT TAG 106534210 8699 60.5CAA CAA CCT TGA A AJ_P2 85652962 G05 AJ_173 /5AmMC6/CCC AAT ACC GAA GAG106534211 8761 60.1 TGC TAG GTT TCA A AJ_P2 85652963 G06 AJ_174/5AmMC6/CCC AAG ACA TAG TAC 106534212 8666 61.6 CGT TGC TAC CCA A AJ_P285652964 G07 AJ_175 /5AmMC6/CCC AAG GTC TAG TAA 106534213 8739 59.7CGA AGC AAC CTA A AJ_P2 85652965 G08 AJ_176 /5AmMC6/CCC AAT AAG CAA CAA106534214 8723 60.1 AGG TCA TTG CCA A AJ_P2 85652966 G09 AJ_177/5AmMC6/CCC AAC TGA GTG AGA 106534215 8779 59.5 AGT CAG AAC CTA A AJ_P285652967 G10 AJ_178 /5AmMC6/CCC AAC TTC GAG TGA 106534216 8723 58.8AAC AAG AAC CTA A AJ_P2 85652968 G11 AJ_179 /5AmMC6/CCC AAA GCG TTC ATG106534217 8727 59.4 GTT CTG TCA TAA A AJ_P2 85652969 G12 AJ_180/5AmMC6/CCC AAG AGG TCT AGG 106534218 8752 59.7 CTT TCG TCT AAA A AJ_P285652970 H01 AJ_181 /5AmMC6/CCC AAA GCC ATT AGT 106534219 8712 60.7CGT GTC GTT ACA A AJ_P2 85652971 H02 AJ_182 /5AmMC6/CCC AAG GTC TTA CGT106534220 8777 61.9 AGG TTG AAG CCA A AJ_P2 85652972 H03 AJ_183/5AmMC6/CCC AAG AGC TTA GCG 106534221 8739 60.2 AAC TTA GAA CCA A AJ_P285652973 H04 AJ_184 /5AmMC6/CCC AAT GGA ACC CTA 106534222 8777 61.9GGG TTG AGT TCA A AJ_P2 85652974 H05 AJ_185 /5AmMC6/CCC AAG AAC ACT TGA106534223 8730 61 GCA GAC GTT TCA A AJ_P2 85652975 H06 AJ_186/5AmMC6/CCC AAT CGA AGG AAA 106534224 8763 58.8 GCA TGA CTC TAA A AJ_P285652976 H07 AJ_187 /5AmMC6/CCC AAC TTA GTG AGA 106534225 8761 59.3GTG CTA CTC AGA A AJ_P2 85652977 H08 AJ_188 /5AmMC6/CCC AAA CTT GTT GAA106534226 8736 59.7 GTG CTT CAC AGA A AJ_P2 85652978 H09 AJ_189/5AmMC6/CCC AAG TGC TAA CAC 106534227 8672 60.5 TGT TCT CCA TGA A AJ_P285652979 H10 AJ_190 /5AmMC6/CCC AAC CCT TAG ACC 106534228 8666 61.7TGA ACA TCG TGA A AJ_P2 85652980 H11 AJ_191 /5AmMC6/CCC AAC TTA AAG GGT106534229 8770 59.2 AGA CCT AGT CGA A AJ_P2 85652981 H12 AJ_192/5AmMC6/CCC AAG GCA TAG ACC 106534230 8712 60.1 TGT CGT TCT TAA A AJ_P385652983 A01 AJ_193 /5AmMC6/CCC AAA GCG TTT CTA 106534231 8761 60.1GGG TAG TAA CCA A AJ_P3 85652984 A02 AJ_194 /5AmMC6/CCC AAG CAA ACT TTC106534232 8705 59.7 CAA GAC GTT GTA A AJ_P3 85652985 A03 AJ_195/5AmMC6/CCC AAT CTG GTA ACT 106534233 8672 60.8 GCT TTC GAA CCA A AJ_P385652986 A04 AJ_196 /5AmMC6/CCC AAT CAG GAG AGC 106534234 8779 59.4AAG TAC TAG TCA A AJ_P3 85652987 A05 AJ_197 /5AmMC6/CCC AAA CAT TGT GTC106534235 8687 59.9 GTT AAC GCT TCA A AJ_P3 85652988 A06 AJ_198/5AmMC6/CCC AAG AGG TAC TTA 106534236 8770 59.5 GGC ATA ACC GTA A AJ_P385652989 A07 AJ_199 /5AmMC6/CCC AAA AAC GGT TTG 106534237 8739 62.2GCA AAC TGA CCA A AJ_P3 85652990 A08 AJ_200 /5AmMC6/CCC AAC ATA AGG CAA106534238 8755 62.1 GGG TAC TGT CCA A AJ_P3 85652991 A09 AJ_201/5AmMC6/CCC AAA TGA CGA CAG 106534239 8795 61.6 GAG TAG TGT CCA A AJ_P385652992 A10 AJ_202 /5AmMC6/CCC AAG ACC TTT GCG 106534240 8712 60.4TTT ACA GGA CTA A AJ_P3 85652993 A11 AJ_203 /5AmMC6/CCC AAG TCT AGA GTC106534241 8699 59.6 AAC ACA GCA CTA A AJ_P3 85652994 A12 AJ_204/5AmMC6/CCC AAG AGA GCT TAA 106534242 8715 61.5 CCA GAC TGT CCA A AJ_P385652995 B01 AJ_205 /5AmMC6/CCC AAG ACC ATA CTG 106534243 8690 60.1CAC ATT AGG CTA A AJ_P3 85652996 B02 AJ_206 /5AmMC6/CCC AAG CCA ACT ACG106534244 8706 61.8 TCA TAG TGG TCA A AJ_P3 85652997 B03 AJ_207/5AmMC6/CCC AAT GTC GAA CGT 106534245 8699 60.2 ACC AAG ACC ATA A AJ_P385652998 B04 AJ_208 /5AmMC6/CCC AAC GTG TAG GAA 106534246 8761 60GTT CGT ACT CAA A AJ_P3 85652999 B05 AJ_209 /5AmMC6/CCC AAA AAC CGT AAG106534247 8730 61.3 CCT TCA TGG TGA A AJ_P3 85653000 B06 AJ_210/5AmMC6/CCC AAT CGG AAA CGC 106534248 8745 59.7 AAG TTC ATG TTA A AJ_P385653001 B07 AJ_211 /5AmMC6/CCC AAT CGG TAA CTA 106534249 8763 58.3GAA AGC ACA GTA A AJ_P3 85653002 B08 AJ_212 /5AmMC6/CCC AAG TCG AAG TAG106534250 8779 60.1 GCT AAA GTC CAA A AJ_P3 85653003 B09 AJ_213/5AmMC6/CCC AAA CGG TAG TAC 106534251 8712 59.8 CTT GTC GTC ATA A AJ_P385653004 B10 AJ_214 /5AmMC6/CCC AAC ATT TGG AAG 106534252 8727 59.6TTG CAT CCT GTA A AJ_P3 85653005 B11 AJ_215 /5AmMC6/CCC AAC GAA GTG TTG106534253 8746 62.6 GTC AAG TCC ACA A AJ_P3 85653006 B12 AJ_216/5AmMC6/CCC AAT CAA GGA AAG 106534254 8779 60.5 GAC TAG TTC GCA A AJ_P385653007 C01 AJ_217 /5AmMC6/CCC AAC GAA ACT TAC 106534255 8723 58.3AAC GTA GGA CTA A AJ_P3 85653008 C02 AJ_218 /5AmMC6/CCC AAG GCA TGC TTA106534256 8727 59 GTC TGA ACT TTA A AJ_P3 85653009 C03 AJ_219/5AmMC6/CCC AAG AAC CGT TCC 106534257 8672 60.5 CAT GTA GCT TTA A AJ_P385653010 C04 AJ_220 /5AmMC6/CCC AAG GCA TAA AGT 106534258 8745 59.1GTT CTC TCG AAA A AJ_P3 85653011 C05 AJ_221 /5AmMC6/CCC AAG GCT ACC CTT106534259 8739 59.6 AAA GAG GAC ATA A AJ_P3 85653012 C06 AJ_222/5AmMC6/CCC AAG TCC TAG ACT 106534260 8712 59.8 TCG GTT CGT AAA A AJ_P385653013 C07 AJ_223 /5AmMC6/CCC AAG GAA CCT TGT 106534261 8699 60.2ACA ACA CGA CTA A AJ_P3 85653014 C08 AJ_224 /5AmMC6/CCC AAC ACG TTG TAG106534262 8779 59.3 AGA CAG AGA CTA A AJ_P3 85653015 C09 AJ_225/5AmMC6/CCC AAT CCA AGC ACA 106534263 8730 61 AGG TAG GTT TCA A AJ_P385653016 C10 AJ_226 /5AmMC6/CCC AAA GCC ATA CTA 106534264 8736 59GTT GTT GTC GAA A AJ_P3 85653017 C11 AJ_227 /5AmMC6/CCC AAC GAG TAC CAT106534265 8779 59.2 AGT GAA GGA CTA A AJ_P3 85653018 C12 AJ_228/5AmMC6/CCC AAC ATT TGC CAA 106534266 8770 60.3 GGG TAG AGA CTA A AJ_P385653019 D01 AJ_229 /5AmMC6/CCC AAC GAC TGT TTC 106534267 8687 59.3CGT AAA GCT TTA A AJ_P3 85653020 D02 AJ_230 /5AmMC6/CCC AAG GAG TAC GAG106534268 8779 59.7 ACA TCA AGC TTA A AJ_P3 85653021 D03 AJ_231/5AmMC6/CCC AAT GGA CTG TCT 106534269 8777 61.6 GGA GTA ACG TCA A AJ_P385653022 D04 AJ_232 /5AmMC6/CCC AAA CCG TTA CAG 106534270 8752 60.5GTT TAG TGT CGA A AJ_P3 85653023 D05 AJ_233 /5AmMC6/CCC AAT GAC AAA GAG106534271 8763 58.6 TAC GAA CTG CTA A AJ_P3 85653024 D06 AJ_234/5AmMC6/CCC AAT CAC AAG TGA 106534272 8723 59 CAA AGT ACG CTA A AJ_P385653025 D07 AJ_235 /5AmMC6/CCC AAC TGT AAA GAG 106534273 8736 58.1TTG CTA GCT CTA A AJ_P3 85653026 D08 AJ_236 /5AmMC6/CCC AAT GGG AAC ACT106534274 8795 62.3 GTG AAG TCG ACA A AJ_P3 85653027 D09 AJ_237/5AmMC6/CCC AAA TTG CGT TTG 106534275 8752 61.9 GTC AAC TGG ACA A AJ_P385653028 D10 AJ_238 /5AmMC6/CCC AAC GAA GGT TCA 106534276 8746 62GGT TAG TCC ACA A AJ_P3 85653029 D11 AJ_239 /5AmMC6/CCC AAA TGC TGT GTT106534277 8687 59.7 AAC CTT TAG CCA A AJ_P3 85653030 D12 AJ_240/5AmMC6/CCC AAC CAC TTG TAG 106534278 8712 59.5 TAC TAG GTT CGA A AJ_P385653031 E01 AJ_241 /5AmMC6/CCC AAC CCA TAG AGG 106534279 8712 60.3TTT CAC GTT GTA A AJ_P3 85653032 E02 AJ_242 /5AmMC6/CCC AAC TAG GAA AGA106534280 8763 58.7 GTT CAA CGC ATA A AJ_P3 85653033 E03 AJ_243/5AmMC6/CCC AAT CCG AAG AAA 106534281 8779 59.6 GGT CTA CAG GTA A AJ_P385653034 E04 AJ_244 /5AmMC6/CCC AAT GGA AAC CCT 106534282 8714 58.9TAA GAA CTG CTA A AJ_P3 85653035 E05 AJ_245 /5AmMC6/CCC AAG CAA CAT AAC106534283 8699 60.5 CTT GAC TCA GGA A AJ_P3 85653036 E06 AJ_246/5AmMC6/CCC AAT AGA ACC ACA 106534284 8723 58.4 GAC TTT AGC AGA A AJ_P385653037 E07 AJ_247 /5AmMC6/CCC AAT CAC AAG AGG 106534285 8763 59.1TTC GTA CGA AAA A AJ_P3 85653038 E08 AJ_248 /5AmMC6/CCC AAA GCT TTG TCT106534286 8705 59.3 CCA GTA CGA AAA A AJ_P3 85653039 E09 AJ_249/5AmMC6/CCC AAT CGG AAG GTG 106534287 8770 60.7 TTC AGT AAA CCA A AJ_P385653040 E10 AJ_250 /5AmMC6/CCC AAA GTG CAT TCC 106534288 8723 59.4AAG AAA CGA CTA A AJ_P3 85653041 E11 AJ_251 /5AmMC6/CCC AAG ACG TAA CCA106534289 8690 60.1 TCG AAC TCG TTA A AJ_P3 85653042 E12 AJ_252/5AmMC6/CCC AAC CGT AGA ACG 106534290 8687 59.3 TTC TTT GCT TAA A AJ_P385653043 F01 AJ_253 /5AmMC6/CCC AAG AGC TCA AGG 106534291 8755 61.6GTT CTA GAA CCA A AJ_P3 85653044 F02 AJ_254 /5AmMC6/CCC AAT CGG TAG TTA106534292 8770 60 CGA GTA AAG CCA A AJ_P3 85653045 F03 AJ_255/5AmMC6/CCC AAG ACA ACT AGC 106534293 8666 61.5 TCT TGG ACT CCA A AJ_P385653046 F04 AJ_256 /5AmMC6/CCC AAT GAC GAA GGA 106534294 8739 59.5CAC TTA GAC CTA A AJ_P3 85653047 F05 AJ_257 /5AmMC6/CCC AAC CGT AGA ACA106534295 8714 59.1 TTT GAA GCC ATA A AJ_P3 85653048 F06 AJ_258/5AmMC6/CCC AAC CAC TCG AAC 106534296 8675 62.2 ATG GTA ACG TCA A AJ_P385653049 F07 AJ_259 /5AmMC6/CCC AAT CGA ACC GTA 106534297 8690 60.7ACC ATT TCA GGA A AJ_P3 85653050 F08 AJ_260 /5AmMC6/CCC AAC TAG TGG TTG106534298 8761 60.5 GAA CAT GCA CTA A AJ_P3 85653051 F09 AJ_261/5AmMC6/CCC AAG TGC TTA CTG 106534299 8721 60.8 TCC ATC GGA AAA A AJ_P385653052 F10 AJ_262 /5AmMC6/CCC AAT GAG TCT GCA 106534300 8687 58.8TCT CTT TCA AGA A AJ_P3 85653053 F11 AJ_263 /5AmMC6/CCC AAT AGG ACA AAG106534301 8739 59.8 ACG TCT TAC CGA A AJ_P3 85653054 F12 AJ_264/5AmMC6/CCC AAT CAT AGG CTA 106534302 8779 59.3 AGG GAA GAC CTA A AJ_P385653055 G01 AJ_265 /5AmMC6/CCC AAC AGA GGT AAA 106534303 8795 61.7GTC CAG TGG TCA A AJ_P3 85653056 G02 AJ_266 /5AmMC6/CCC AAG ACC ACT ACA106534304 8690 60.7 ACG TTG CAT GTA A AJ_P3 85653057 G03 AJ_267/5AmMC6/CCC AAT AGA CCA CAA 106534305 8739 60.2 GCA TCG TTA GGA A AJ_P385653058 G04 AJ_268 /5AmMC6/CCC AAG TCA CTC ACC 106534306 8681 59.8TAA GTT CGG TAA A AJ_P3 85653059 G05 AJ_269 /5AmMC6/CCC AAG CTT TCA AGT106534307 8690 60.3 ACC ACA CGA GTA A AJ_P3 85653060 G06 AJ_270/5AmMC6/CCC AAG TCA CAT CCT 106534308 8697 61.4 CTA GGG TTC GAA A AJ_P385653061 G07 AJ_271 /5AmMC6/CCC AAA AAC GTT CAT 106534309 8736 59.8TTG GTC TGA CGA A AJ_P3 85653062 G08 AJ_272 /5AmMC6/CCC AAC TGT CCA TTC106534310 8730 61.2 GGA ACG TGA AAA A AJ_P3 85653063 G09 AJ_273/5AmMC6/CCC AAA GTT CTT TCT TCA 106534311 8727 59.1 GCA AGG GTA A AJ_P385653064 G10 AJ_274 /5AmMC6/CCC AAT AGT CCT GTC 106534312 8712 59.5GTT AGA ACC GTA A AJ_P3 85653065 G11 AJ_275 /5AmMC6/CCC AAC GTA CAT CCC106534313 8690 60.2 TTA GAA ACG TGA A AJ_P3 85653066 G12 AJ_276/5AmMC6/CCC AAC GGT TCA GCA 106534314 8687 59.7 CTT TAC ATT TGA A AJ_P385653067 H01 AJ_277 /5AmMC6/CCC AAT GCG TAA ACT 106534315 8672 60.7CGT TGT CCT ACA A AJ_P3 85653068 H02 AJ_278 /5AmMC6/CCC AAT CGG TAA ACC106534316 8687 59.4 TGT TTC GCT TAA A AJ_P3 85653069 H03 AJ_279/5AmMC6/CCC AAG TGC AAG CAC 106534317 8770 61.4 AGG TGA CAT TTA A AJ_P385653070 H04 AJ_280 /5AmMC6/CCC AAG GGT ACA GAC 106534318 8795 60.9GAG TAA CTC TGA A AJ_P3 85653071 H05 AJ_281 /5AmMC6/CCC AAA CCC TAG TAG106534319 8672 59.1 TTC TAC TCG TGA A AJ_P3 85653072 H06 AJ_282/5AmMC6/CCC AAG TAA CCC TTC 106534320 8706 61 CGT AGG ACA GTA A AJ_P385653073 H07 AJ_283 /5AmMC6/CCC AAT TTA GTC ACT 106534321 8672 60.3CTG GTC AAC CGA A AJ_P3 85653074 H08 AJ_284 /5AmMC6/CCC AAG TAC ACA ACC106534322 8715 61.6 TCT GGT AAC GGA A AJ_P3 85653075 H09 AJ_285/5AmMC6/CCC AAC ACA AGT TCA 106534323 8795 62.2 GGT AGG AGT GCA A AJ_P385653076 H10 AJ_286 /5AmMC6/CCC AAC TAA AGG TGT 106534324 8696 59.4TTA CGC TTC CAA A AJ_P3 85653077 H11 AJ_287 /5AmMC6/CCC AAC TGA AGT TGG106534325 8777 61.4 TCT ACC TGA GGA A AJ_P3 85653078 H12 AJ_288/5AmMC6/CCC AAT GTC GTA AGT 106534326 8672 60.8 TCC TCA ACT GCA A AJ_P485653080 A01 AJ_289 /5AmMC6/CCC AAA CCT GAG ACC 106534327 8712 60.5TGT GTT TCG TAA A AJ_P4 85653081 A02 AJ_290 /5AmMC6/CCC AAT AGG CTA GCT106534328 8723 58.4 CAA CCA TAA AGA A AJ_P4 85653082 A03 AJ_291/5AmMC6/CCC AAG TTG ACA ACG 106534329 8675 61.8 CTA CCC TAG ACA A AJ_P485653083 A04 AJ_292 /5AmMC6/CCC AAT CAC GAA GTG 106534330 8754 59.7AGC TTG TCA AAA A AJ_P4 85653084 A05 AJ_293 /5AmMC6/CCC AAT GAA ACC GTA106534331 8690 61.2 ACT CAC TTG GCA A AJ_P4 85653085 A06 AJ_294/5AmMC6/CCC AAC TTA GCA CAA 106534332 8763 59.2 AGT GTA GAA GCA A AJ_P485653086 A07 AJ_295 /5AmMC6/CCC AAT GCG TAG AAC 106534333 8763 59.1CAT GTA CAA AGA A AJ_P4 85653087 A08 AJ_296 /5AmMC6/CCC AAG AGT TGC TTC106534334 8761 60.4 GGT ACT CAA AGA A AJ_P4 85653088 A09 AJ_297/5AmMC6/CCC AAG CGT AGT TCG 106534335 8779 60.3 GAA ACA CTA AGA A AJ_P485653089 A10 AJ_298 /5AmMC6/CCC AAA AGA GTC TTA 106534336 8690 59.4CCG TAC TAC CGA A AJ_P4 85653090 A11 AJ_299 /5AmMC6/CCC AAA AAC GGT AGG106534337 8706 61.7 TCT CTG ACT CCA A AJ_P4 85653091 A12 AJ_300/5AmMC6/CCC AAG GTC AGT TAA 106534338 8706 62.4 GCC AAC CCT TGA A AJ_P485653092 B01 AJ_301 /5AmMC6/CCC AAA CCA GTC TCT 106534339 8672 60.1CAG TTT ACG TGA A AJ_P4 85653093 B02 AJ_302 /5AmMC6/CCC AAT AAG ACA AGG106534340 8699 60.7 ACT TCC ATG CCA A AJ_P4 85653094 B03 AJ_303/5AmMC6/CCC AAG TCG AGA ACA 106534341 8770 59.9 TGG AAG TCC TTA A AJ_P485653095 B04 AJ_304 /5AmMC6/CCC AAT GCA GAG AAA 106534342 8763 58.4GTA CAT ACC GTA A AJ_P4 85653096 B05 AJ_305 /5AmMC6/CCC AAG TGC ACT TAA106534343 8779 60.5 GGA CAA CAG GTA A AJ_P4 85653097 B06 AJ_306/5AmMC6/CCC AAA CCT GTC TTA 106534344 8721 60.2 AGG CAT ACG GTA A AJ_P485653098 B07 AJ_307 /5AmMC6/CCC AAG TCT CTA AGT 106534345 8752 59.6AGG CAT GCT GTA A AJ_P4 85653099 B08 AJ_308 /5AmMC6/CCC AAC GTC TGA CAT106534346 8770 59.8 TGG AGA GAA CTA A AJ_P4 85653100 B09 AJ_309/5AmMC6/CCC AAA AAG CTC ACG 106534347 8696 59.3 TCT TGG TCT TAA A AJ_P485653101 B10 AJ_310 /5AmMC6/CCC AAG GGT AAC AGA 106534348 8770 60CAC TTT AGC GTA A AJ_P4 85653102 B11 AJ_311 /5AmMC6/CCC AAT GAC CTA CGA106534349 8795 60.9 GTG GAG AGT ACA A AJ_P4 85653103 B12 AJ_312/5AmMC6/CCC AAA GCT TGC GAA 106534350 8723 59.2 ACC TAA CTA AGA A AJ_P485653104 C01 AJ_313 /5AmMC6/CCC AAT GTC GAC AGA 106534351 8699 59.6CCA TAC CTA AGA A AJ_P4 85653105 C02 AJ_314 /5AmMC6/CCC AAG GTC AAC AAG106534352 8675 62.6 CCA TAC GTT CCA A AJ_P4 85653106 C03 AJ_315/5AmMC6/CCC AAC TGG TTA CTA 106534353 8770 59.5 CGA ACA GGA GTA A AJ_P485653107 C04 AJ_316 /5AmMC6/CCC AAT AGA GAC GTT 106534354 8690 59.1ACT CCT AAC CGA A AJ_P4 85653108 C05 AJ_317 /5AmMC6/CCC AAA GAC AGT TGA106534355 8690 60.1 CAC CTT AGC CTA A AJ_P4 85653109 C06 AJ_318/5AmMC6/CCC AAA TCG AGA GTT 106534356 8690 59.8 ACA CCT TAC CGA A AJ_P485653110 C07 AJ_319 /5AmMC6/CCC AAA CAG GTT TCC 106534357 8779 60.4AAG AAC TAG GGA A AJ_P4 85653111 C08 AJ_320 /5AmMC6/CCC AAG ACA GGT AGG106534358 8777 61.2 TCT TGC TAG TCA A AJ_P4 85653112 C09 AJ_321/5AmMC6/CCC AAG GAG TCT CAA 106534359 8715 61.7 CCG TTA ACC AGA A AJ_P485653113 C10 AJ_322 /5AmMC6/CCC AAG AAA CGT ACG 106534360 8681 60.7CTT CTC CAT TGA A AJ_P4 85653114 C11 AJ_323 /5AmMC6/CCC AAC TTA GGA AGC106534361 8675 61.5 ACT ACG TAC CCA A AJ_P4 85653115 C12 AJ_324/5AmMC6/CCC AAG TAA GCT ACG 106586457 8657 61.5 TTC CTG TAC CCA A AJ_P485653116 D01 AJ_325 /5AmMC6/CCC AAC CAA GTA AGT 106534363 8795 62.1GGA CAC TGG TGA A AJ_P4 85653117 D02 AJ_326 /5AmMC6/CCC AAC TGT TTA CAG106534364 8761 60 AGG TCA GCA GTA A AJ_P4 85653118 D03 AJ_327/5AmMC6/CCC AAC ACG TCT TAA 106534365 8723 58.6 AGC AGA GAA CTA A AJ_P485653119 D04 AJ_328 /5AmMC6/CCC AAG AGG ACT GTC 106534366 8697 61.1CTA CTT CCA TGA A AJ_P4 85653120 D05 AJ_329 /5AmMC6/CCC AAG AAC ATC TCC106534367 8666 61.6 ACT GGT CAC GTA A AJ_P4 85653121 D06 AJ_330/5AmMC6/CCC AAT GAA GCA ACA 106534368 8739 60.9 AGT GGT ACT CCA A AJ_P485653122 D07 AJ_331 /5AmMC6/CCC AAT CCG TAA CAG 106534369 8779 59.5TAG GAG AAC GTA A AJ_P4 85653123 D08 AJ_332 /5AmMC6/CCC AAA CCG TAG GAA106534370 8690 60 CTA CCA TTC TGA A AJ_P4 85653124 D09 AJ_333/5AmMC6/CCC AAC CAG TTC GTT 106534371 8690 60.8 CAA ACA GAC TGA A AJ_P485653125 D10 AJ_334 /5AmMC6/CCC AAG TTA AAC ATC 106534372 8699 60.4CAG AGC TCA CGA A AJ_P4 85653126 D11 AJ_335 /5AmMC6/CCC AAG TCA CAC AAC106534373 8715 61.9 CTA GAG CTT GGA A AJ_P4 85653127 D12 AJ_336/5AmMC6/CCC AAC ATG TTA GGG 106534374 8752 61 TTA CCT TGG CAA A AJ_P485653128 E01 AJ_337 /5AmMC6/CCC AAG TCA AAG GTA 106534375 8666 61.7CTC CAC TTC CGA A AJ_P4 85653129 E02 AJ_338 /5AmMC6/CCC AAG TAG AAC GTC106534376 8699 60 AAC CAC TTA CGA A AJ_P4 85653130 E03 AJ_339/5AmMC6/CCC AAG GAG ACT TGT 106534377 8697 60.5 CCT ACT CTA CGA A AJ_P485653131 E04 AJ_340 /5AmMC6/CCC AAT TTC GTA GTA 106534378 8687 58.9CTC ACT TGC GAA A AJ_P4 85653132 E05 AJ_341 /5AmMC6/CCC AAC CTT GTA CTA106534379 8770 59.5 GGA AGG AAG CTA A AJ_P4 85653133 E06 AJ_342/5AmMC6/CCC AAG TCG TAG TTG 106534380 8697 62.3 TCA CAC TGC ACA A AJ_P485653134 E07 AJ_343 /5AmMC6/CCC AAC GAA GTT ACG 106534381 8672 61TCT TTC ATG CCA A AJ_P4 85653135 E08 AJ_344 /5AmMC6/CCC AAA AGG CAT AAG106534382 8730 61.3 GCT TGT CAT CCA A AJ_P4 85653136 E09 AJ_345/5AmMC6/CCC AAG TGT CCA TAC 106534383 8681 60.8 GCT TTA CCG AAA A AJ_P485653137 E10 AJ_346 /5AmMC6/CCC AAC GGT TGA CAC 106534384 8715 62.3CAG TTA CCA AGA A AJ_P4 85653138 E11 AJ_347 /5AmMC6/CCC AAG TGT GCA ACC106534385 8697 62.2 AGT TAC TCC TGA A AJ_P4 85653139 E12 AJ_348/5AmMC6/CCC AAG CTG ACA GAC 106534386 8672 60.1 TCT CTT TCA TGA A AJ_P485653140 F01 AJ_349 /5AmMC6/CCC AAG AAA GCT GTA 106534387 8681 59.4CCC TTC TCT AGA A AJ_P4 85653141 F02 AJ_350 /5AmMC6/CCC AAA TGT TGC TAC106534388 8714 59 AAG ACT AAC CGA A AJ_P4 85653142 F03 AJ_351/5AmMC6/CCC AAG TCT GGA AGT 106534389 8777 61.4 GCT AGT ACG TCA A AJ_P485653143 F04 AJ_352 /5AmMC6/CCC AAT CGC AAC TTC 106534390 8687 59.4GGT ACA TTT GTA A AJ_P4 85653144 F05 AJ_353 /5AmMC6/CCC AAC CTG TAA CAT106534391 8754 59 TGA AGA AGC GTA A AJ_P4 85653145 F06 AJ_354/5AmMC6/CCC AAA CTG TTG GAA 106534392 8754 59.4 AGC TGA ACA CTA A AJ_P485653146 F07 AJ_355 /5AmMC6/CCC AAG ACG TAG CTT 106534393 8779 58.9AGA GAG AAC CTA A AJ_P4 85653147 F08 AJ_356 /5AmMC6/CCC AAC ATT GTT GTG106534394 8761 60.7 GAA CCT CAG AGA A AJ_P4 85653148 F09 AJ_357/5AmMC6/CCC AAG TGG ACT AGC 106534395 8697 61.2 TTC CTA CAC TGA A AJ_P485653149 F10 AJ_358 /5AmMC6/CCC AAA GGA ACT GAC 106534396 8723 59.2ATT CAA CAC GTA A AJ_P4 85653150 F11 AJ_359 /5AmMC6/CCC AAT GTT CGA GTC106534397 8690 60.2 CAC AAC TAC AGA A AJ_P4 85653151 F12 AJ_360/5AmMC6/CCC AAG TAA CTA CTC 106534398 8739 59 ACA GAG CTA GGA A AJ_P485653152 G01 AJ_361 /5AmMC6/CCC AAG AGG ACT CAC 106534399 8706 61.2CAG TAC TTT CGA A AJ_P4 85653153 G02 AJ_362/5AmMC6/CCC AAT AGC GTT GTT TCT 106534400 8687 59 AAC CAC TGA A AJ_P485653154 G03 AJ_363 /5AmMC6/CCC AAC ATT TGT TAG 106534401 8736 59TAG CAG TCA CGA A AJ_P4 85653155 G04 AJ_364 /5AmMC6/CCC AAT AAC AGC AAG106534402 8699 60.8 ACC TTG TAG CCA A AJ_P4 85653156 G05 AJ_365/5AmMC6/CCC AAG ACT CTC CAC 106534403 8675 61.9 ACG TTG AAG ACA A AJ_P485653157 G06 AJ_366 /5AmMC6/CCC AAG AAC TCC ATC 106534404 8666 61.7CTG TTC GAC AGA A AJ_P4 85653158 G07 AJ_367 /5AmMC6/CCC AAG GTT CTA GTT106534405 8681 60.4 CCA ACT AAC GCA A AJ_P4 85653159 G08 AJ_368/5AmMC6/CCC AAA GTT GCG TTT 106534406 8727 59 GTC ATA GAC CTA A AJ_P485653160 G09 AJ_369 /5AmMC6/CCC AAC GCT TGA GGT 106534407 8763 59AAA CTA AAC AGA A AJ_P4 85653161 G10 AJ_370 /5AmMC6/CCC AAT AAC GAG TAG106534408 8739 59 AGC TCT AGA CCA A AJ_P4 85653162 G11 AJ_371/5AmMC6/CCC AAG TGA GTC ATA 106534409 8739 60.5 GCC ATA AGC CAA A AJ_P485653163 G12 AJ_372 /5AmMC6/CCC AAC TTA CGT GAC 106534410 8672 60.3TTC CAT TCA GGA A AJ_P4 85653164 H01 AJ_373 /5AmMC6/CCC AAA TCA GTG ACT106534411 8672 60.1 GTC TCT TCA CGA A AJ_P4 85653165 H02 AJ_374/5AmMC6/CCC AAA GGT ACT GAC 106534412 8657 61.4 TTC CAC TCC TGA A AJ_P485653166 H03 AJ_375 /5AmMC6/CCC AAT CGA CAT TAC 106534413 8779 59.9AGG AAG TAC GGA A AJ_P4 85653167 H04 AJ_376 /5AmMC6/CCC AAC CAC TGG TTA106534414 8739 60.9 AAC GTA AAC GGA A AJ_P4 85653168 H05 AJ_377/5AmMC6/CCC AAG TTC ATT CCC 106534415 8672 60.7 TAA GCC TTG GAA A AJ_P485653169 H06 AJ_378 /5AmMC6/CCC AAG AAA CTA CTC 106534416 8730 60.1CAT GGT TAG CGA A AJ_P4 85653170 H07 AJ_379 /5AmMC6/CCC AAC TAA GGG TTA106534417 8745 58.4 AAG CTT ACC GTA A AJ_P4 85653171 H08 AJ_380/5AmMC6/CCC AAG AGA CCT GTC 106534418 8690 60.1 ACA CTT TAA CGA A AJ_P485653172 H09 AJ_381 /5AmMC6/CCC AAT GAA CAA CAA 106534419 8723 59.8CAT GCT TAC GGA A AJ_P4 85653173 H10 AJ_382 /5AmMC6/CCC AAT CAG AAA GCA106534420 8763 58.9 ACA TTC TAG GGA A AJ_P4 85653174 H11 AJ_383/5AmMC6/CCC AAT AGG CTT GAC 106534421 8705 58.8 TCA TTA AAC CGA A AJ_P485653175 H12 AJ_384 /5AmMC6/CCC AAA CTG GTT TGT 106534422 8712 60.3AGT CCT ACC GAA A AJ_P5 85653177 A01 AJ_385 /5AmMC6/CCC AAA CCT GAC AGC106534423 8687 59 TTG TTT CTT AGA A AJ_P5 85653178 A02 AJ_386/5AmMC6/CCC AAC TTG CTA CAT 106534424 8770 59.9 AGA GAG AGT GCA A AJ_P585653179 A03 AJ_387 /5AmMC6/CCC AAG GTA AAC CTT 106534425 8666 61.5CCA GTC TCC AGA A AJ_P5 85653180 A04 AJ_388 /5AmMC6/CCC AAT ACC AAG TAC106534426 8739 60.8 GCA AAC TGT GGA A AJ_P5 85653181 A05 AJ_389/5AmMC6/CCC AAC CGT AAA CCT 106534427 8730 60.5 TAA GGT GTA GCA A AJ_P585653182 A06 AJ_390 /5AmMC6/CCC AAC ATT GTT TCC 106534428 8681 61.6CAA GGC ATA GCA A AJ_P5 85653183 A07 AJ_391 /5AmMC6/CCC AAG GTC ATC CTA106534429 8657 61.9 CTA GCA TTG CCA A AJ_P5 85653184 A08 AJ_392/5AmMC6/CCC AAG TTC AAC ATC 106534430 8681 60.4 ACT GCT ACG GTA A AJ_P585653185 A09 AJ_393 /5AmMC6/CCC AAT TCG CAT GCA 106534431 8727 60.1TTT AAG GTG TCA A AJ_P5 85653186 A10 AJ_394 /5AmMC6/CCC AAC TTA GCA CTA106534432 8779 59.4 GAG AAG GAG TCA A AJ_P5 85653187 A11 AJ_395/5AmMC6/CCC AAG CTC AGG ACA 106534433 8777 62.2 GTT GAG TGT TCA A AJ_P585653188 A12 AJ_396 /5AmMC6/CCC AAG TCC TAG CTA 106534434 8761 59.7AGA GTG TGT CAA A AJ_P5 85653189 B01 AJ_397 /5AmMC6/CCC AAG CTA CAA GCA106534435 8754 59.3 TAA GTG GTT CAA A AJ_P5 85653190 B02 AJ_398/5AmMC6/CCC AAG TCA TAC CAA 106534436 8739 60 AGC TGA GAC GTA A AJ_P585653191 B03 AJ_399 /5AmMC6/CCC AAT TTA GCA TAG 106534437 8754 58ACG AGA GAC TCA A AJ_P5 85653192 B04 AJ_400 /5AmMC6/CCC AAT TTC ATG TAA106534438 8745 59.4 CGA CAG TGA GCA A AJ_P5 85653193 B05 AJ_401/5AmMC6/CCC AAT GCA CTT CGT 106534439 8754 58.6 AGA GTA AGA ACA A AJ_P585653194 B06 AJ_402 /5AmMC6/CCC AAA CGT TGT CTC 106534440 8752 60.5TGT AGT GGA ACA A AJ_P5 85653195 B07 AJ_403 /5AmMC6/CCC AAC CGA AGT TAG106534441 8699 60.8 CAA ACC TCA TGA A AJ_P5 85653196 B08 AJ_404/5AmMC6/CCC AAC ATT TAG AAG 106534442 8754 58.8 GAC TTC GAA CGA A AJ_P585653197 B09 AJ_405 /5AmMC6/CCC AAG TTC CAA CAC 106534443 8675 62TCA GAC AGG TCA A AJ_P5 85653198 B10 AJ_406 /5AmMC6/CCC AAT GAC AAC CTC106534444 8706 61.7 TCA GAG TGG TCA A AJ_P5 85653199 B11 AJ_407/5AmMC6/CCC AAG CCT AGG TAG 106534445 8777 61 GTT CTG GAA CTA A AJ_P585653200 B12 AJ_408 /5AmMC6/CCC AAT CGA ACA CAC 106534446 8690 60.6CAT GTT ACT GGA A AJ_P5 85653201 C01 AJ_409 /5AmMC6/CCC AAT AGT CTA ACT106534447 8727 59.3 GTT GGC TTG CAA A AJ_P5 85653202 C02 AJ_410/5AmMC6/CCC AAA AGC TAG GTA 106534448 8681 59.8 CCT TCT TAC CGA A AJ_P585653203 C03 AJ_411 /5AmMC6/CCC AAC TCA GAG TAC 106534449 8770 60AGA GAG TTT GCA A AJ_P5 85653204 C04 AJ_412 /5AmMC6/CCC AAG ACA CGT CAT106534450 8795 61.4 AGG AGT GTA GCA A AJ_P5 85653205 C05 AJ_413/5AmMC6/CCC AAT TAA GCA TAA 106534451 8763 59.2 CGA GAC AGT GCA A AJ_P585653206 C06 AJ_414 /5AmMC6/CCC AAG TGT CCA CAT 106534452 8795 62.6GAG GTG AAA GCA A AJ_P5 85653207 C07 AJ_415 /5AmMC6/CCC AAC TAA AGG GTT106534453 8770 60.6 GAA CGT TCC AGA A AJ_P5 85653208 C08 AJ_416/5AmMC6/CCC AAA TCG CTT TCT TTA 106534454 8727 59.1 GTG GAG ACA A AJ_P585653209 C09 AJ_417 /5AmMC6/CCC AAA GGT CTT CAC 106534455 8696 60.1TTT GTG CAC AAA A AJ_P5 85653210 C10 AJ_418 /5AmMC6/CCC AAG GCT TAA GGT106534456 8755 62.3 GAA CCA TCG ACA A AJ_P5 85653211 C11 AJ_419/5AmMC6/CCC AAC TGT AGA GCT 106534457 8699 59.3 ACC AAC ACT AGA A AJ_P585653212 C12 AJ_420 /5AmMC6/CCC AAC TAA GGG TTG 106534458 8752 60.5TTA CGT TAG CCA A AJ_P5 85653213 D01 AJ_421 /5AmMC6/CCC AAG TGG TAC TCA106534459 8697 61.4 GCT ACA TCG TCA A AJ_P5 85653214 D02 AJ_422/5AmMC6/CCC AAG TCC AAA CAC 106534460 8675 62.3 CTT GAG AGC TCA A AJ_P585653215 D03 AJ_423 /5AmMC6/CCC AAT CAC AAG CTT 106534461 8779 60.1AGA GTG GAG ACA A AJ_P5 85653216 D04 AJ_424 /5AmMC6/CCC AAC TTT GAC TTT106534462 8752 60.9 GGC AAC TAG GGA A AJ_P5 85653217 D05 AJ_425/5AmMC6/CCC AAC CTC AGT CTA 106534463 8737 61 AGG GTA GTG TCA A AJ_P585653218 D06 AJ_426 /5AmMC6/CCC AAA CAC CTG TCC 106534464 8715 61.6AGA GAG TGT ACA A AJ_P5 85653219 D07 AJ_427 /5AmMC6/CCC AAC ATA GTT GTG106534465 8745 59.2 AAG CAT CGC TAA A AJ_P5 85653220 D08 AJ_428/5AmMC6/CCC AAA CGT GTT GTT 106534466 8752 60.6 GTA CCC TAG GAA A AJ_P585653221 D09 AJ_429 /5AmMC6/CCC AAA CTT TGG TAG 106534467 8754 59.4AAA CGT AGC CAA A AJ_P5 85653222 D10 AJ_430 /5AmMC6/CCC AAC TCA GTT GCA106534468 8736 59.9 TTA AAG TGT GCA A AJ_P5 85653223 D11 AJ_431/5AmMC6/CCC AAA CTA CTG TTC 106534469 8712 60.2 TGG ACT TCG GAA A AJ_P585653224 D12 AJ_432 /5AmMC6/CCC AAA GAG CAT TAG 106534470 8779 60GAC TGT ACG ACA A AJ_P5 85653225 E01 AJ_433 /5AmMC6/CCC AAC ACC ATG CTG106534471 8746 62.3 AGT GGT AAG TCA A AJ_P5 85653226 E02 AJ_434/5AmMC6/CCC AAC TGG AAC ACG 106534472 8795 62.2 TGT GGT AGA ACA A AJ_P585653227 E03 AJ_435 /5AmMC6/CCC AAC CTC AGA ACT 106534473 8657 62CGT TGG TTA CCA A AJ_P5 85653228 E04 AJ_436 /5AmMC6/CCC AAT GCC ATA ACG106534474 8687 59.3 CTT GTA CTT GTA A AJ_P5 85653229 E05 AJ_437/5AmMC6/CCC AAA ACC TTG TAG 106534475 8763 59 ACA AGA AGC GTA A AJ_P585653230 E06 AJ_438 /5AmMC6/CCC AAC ACA TGT TAG 106534476 8779 59.8AGA CGA CAG GTA A AJ_P5 85653231 E07 AJ_439 /5AmMC6/CCC AAG GTA CTC TAA106534477 8672 59.4 CTT GCA GTC CTA A AJ_P5 85653232 E08 AJ_440/5AmMC6/CCC AAT GCC AAC CTC 106534478 8699 60.9 AAG AAG TGT ACA A AJ_P585653233 E09 AJ_441 /5AmMC6/CCC AAC TAA AGT TGG 106534479 8739 61.2GAA CGC ATC ACA A AJ_P5 85653234 E10 AJ_442 /5AmMC6/CCC AAG GAC TAC TCC106534480 8666 61 ACT GTC ATC AGA A AJ_P5 85653235 E11 AJ_443/5AmMC6/CCC AAG AAC CGT AGT 106534481 8657 61 TCC TTC CCT AGA A AJ_P585653236 E12 AJ_444 /5AmMC6/CCC AAC TTT GAG GTG 106534482 8752 60.1AGA CTC GTT ACA A AJ_P5 85653237 F01 AJ_445 /5AmMC6/CCC AAT CAG AGA AGA106534483 8739 60.1 GTT CGT CAC ACA A AJ_P5 85653238 F02 AJ_446/5AmMC6/CCC AAG TTT CAT TCC TCA 106534484 8672 60.5 GAG CTG ACA A AJ_P585653239 F03 AJ_447 /5AmMC6/CCC AAG TTG TCA CTC 106534485 8657 61.8CTG AGC ACT ACA A AJ_P5 85653240 F04 AJ_448 /5AmMC6/CCC AAA AGG TTC ATC106534486 8681 61.5 GCT TTG ACC ACA A AJ_P5 85653241 F05 AJ_449/5AmMC6/CCC AAT GCC AAG ACT 106534487 8752 61.2 TGT GGT GTT ACA A AJ_P585653242 F06 AJ_450 /5AmMC6/CCC AAA GGC TTC GGT 106534488 8739 60.4AAC ACT AAC AGA A AJ_P5 85653243 F07 AJ_451 /5AmMC6/CCC AAC AGC TAG CAT106534489 8752 61.1 GGT TTG GTT ACA A AJ_P5 85653244 F08 AJ_452/5AmMC6/CCC AAG CCA TTA GCC 106534490 8657 62.2 TAG TTG TCC ACA A AJ_P585653245 F09 AJ_453 /5AmMC6/CCC AAC GGT ACA ACG 106534491 8777 62.7GTT GGG TTT ACA A AJ_P5 85653246 F10 AJ_454 /5AmMC6/CCC AAC ACC AGT TGG106534492 8715 62.5 ACA GGA CAT TCA A AJ_P5 85653247 F11 AJ_455/5AmMC6/CCC AAT CTC AGA CTG 106534493 8786 61.8 GAA GGG TTG ACA A AJ_P585653248 F12 AJ_456 /5AmMC6/CCC AAG TGT GAC GAA 106534494 8739 60.9CCT CAA ACA TGA A AJ_P5 85653249 G01 AJ_457 /5AmMC6/CCC AAT GCG TAC AGG106534495 8779 60.1 TAC ATA GGA CAA A AJ_P5 85653250 G02 AJ_458/5AmMC6/CCC AAC AGT TAA AGG 106534496 8763 59.1 ACA TGA GCT CAA A AJ_P585653251 G03 AJ_459 /5AmMC6/CCC AAT CCG AAA GGG 106534497 8770 60.3TTA CAG TTA CGA A AJ_P5 85653252 G04 AJ_460 /5AmMC6/CCC AAC ATT GTG AAA106534498 8721 61.6 GTG CAG TTC CCA A AJ_P5 85653253 G05 AJ_461/5AmMC6/CCC AAA ACC ATG AGG 106534499 8675 62.5 TCA CGT TAC CCA A AJ_P585653254 G06 AJ_462 /5AmMC6/CCC AAT CAA GGA GAA 106534500 8739 60.3ACG TGT ACC TCA A AJ_P5 85653255 G07 AJ_463 /5AmMC6/CCC AAT CAG GAG ACG106534501 8795 60.6 ACT AGT AGG TCA A AJ_P5 85653256 G08 AJ_464/5AmMC6/CCC AAG GAC TAG GTC 106534502 8706 61 ACA CAT CTC TGA A AJ_P585653257 G09 AJ_465 /5AmMC6/CCC AAC ATA GAG AGG 106534503 8739 59.5ACA TCT TCG ACA A AJ_P5 85653258 G10 AJ_466 /5AmMC6/CCC AAC GAA CTC ATC106534504 8666 62.3 CTT GTG GAC ACA A AJ_P5 85653259 G11 AJ_467/5AmMC6/CCC AAC AGT TGG TGA 106534505 8761 61.5 GTT CAT GCA CAA A AJ_P585653260 G12 AJ_468 /5AmMC6/CCC AAC ATA GGA CAG 106534506 8795 62.3GAG TGT TGC ACA A AJ_P5 85653261 H01 AJ_469 /5AmMC6/CCC AAC TAG TAG AAG106534507 8779 59.8 ACT GCA TGG ACA A AJ_P5 85653262 H02 AJ_470/5AmMC6/CCC AAT AGA GCA AGA 106534508 8779 60.2 ACC TCA GTT GGA A AJ_P585653263 H03 AJ_471 /5AmMC6/CCC AAC CAT GTG GAG 106534509 8777 62.1TTT CTG AGG ACA A AJ_P5 85653264 H04 AJ_472 /5AmMC6/CCC AAT AGA CAG GAC106534510 8755 61.9 AGG TGT TCC CAA A AJ_P5 85653265 H05 AJ_473/5AmMC6/CCC AAT TCG GAA GCC 106534511 8687 58.8 ATT TCT CTT AGA A AJ_P585653266 H06 AJ_474 /5AmMC6/CCC AAT CGG AAC AGT 106534512 8672 60.3TCC TCA TTC TGA A AJ_P5 85653267 H07 AJ_475 /5AmMC6/CCC AAT GAA GCA GTT106534513 8696 59.2 CCA TCA TTC TGA A AJ_P5 85653268 H08 AJ_476/5AmMC6/CCC AAC ATG TGT CAA 106534514 8737 61.9 GGG TAG CTC TCA A AJ_P585653269 H09 AJ_477 /5AmMC6/CCC AAG CCT TTA CAC 106534515 8666 62.8CAT GTG GAA CCA A AJ_P5 85653270 H10 AJ_478 /5AmMC6/CCC AAC TAA CTG CTG106534516 8786 61.5 AGG TGA GGT ACA A AJ_P5 85653271 H11 AJ_479/5AmMC6/CCC AAC TCC AAG TCG 106534517 8746 61.9 AGT GAG TTG ACA A AJ_P585653272 H12 AJ_480 /5AmMC6/CCC AAC GAG TTG AGA 106534518 8779 60.3AGC TAC ATG ACA A AJ_P6 85653274 A01 AJ_481 /5AmMC6/CCC AAT TTC TGA GTG106534519 8721 60.2 AGC AAC CCT AGA A AJ_P6 85653275 A02 AJ_482/5AmMC6/CCC AAG AGT ACA GCT 106534520 8675 60.8 ACC TCT CCA AGA A AJ_P685653276 A03 AJ_483 /5AmMC6/CCC AAG AGC ACT CCA 106534521 8699 60.4CTT GTA CAA AGA A AJ_P6 85653277 A04 AJ_484 /5AmMC6/CCC AAG CTA CAT TTC106534522 8687 58.3 TTG AGT CGA CTA A AJ_P6 85653278 A05 AJ_485/5AmMC6/CCC AAA CCG TAG GAC 106534523 8699 60.2 TAC AAC ACT TGA A AJ_P685653279 A06 AJ_486 /5AmMC6/CCC AAA TTC CTG TTG 106534524 8752 60.8TGA CGA AGT CGA A AJ_P6 85653280 A07 AJ_487 /5AmMC6/CCC AAA GTT CTG TGG106534525 8752 60.8 TTC ACA AGT CGA A AJ_P6 85653281 A08 AJ_488/5AmMC6/CCC AAG TAC TCG AGT 106534526 8672 59.8 TCC CTT TAA CGA A AJ_P685653282 A09 AJ_489 /5AmMC6/CCC AAG CTG AAG GTT 106534527 8763 59.3AAC AAC AAG CTA A AJ_P6 85653283 A10 AJ_490 /5AmMC6/CCC AAT CGC ATG GTA106534528 8723 59.8 AAC AAA CAC TGA A AJ_P6 85653284 A11 AJ_491/5AmMC6/CCC AAC TGG TAC TAA 106534529 8699 61 AGC CAA ACT GCA A AJ_P685653285 A12 AJ_492 /5AmMC6/CCC AAC GTT AAG AAG 106534530 8730 59.4GTA CCT AGC CTA A AJ_P6 85653286 B01 AJ_493 /5AmMC6/CCC AAC AGT GAA AGT106534531 8721 60.6 TGT CCT TCC AGA A AJ_P6 85653287 B02 AJ_494/5AmMC6/CCC AAC AGG AGT TGG 106534532 8786 61.4 GTA CCA GTC TAA A AJ_P685653288 B03 AJ_495 /5AmMC6/CCC AAG AAA CTG TGC 106534533 8699 61.1AAA CAC TCC TGA A AJ_P6 85653289 B04 AJ_496 /5AmMC6/CCC AAT CGT AGT TCG106534534 8690 60.1 ACA AAC TCC AGA A AJ_P6 85653290 B05 AJ_497/5AmMC6/CCC AAC AGG TTA GTT 106534535 8666 62.1 CAC ACC ATC CGA A AJ_P685653291 B06 AJ_498 /5AmMC6/CCC AAG GTT TAC GTC 106534536 8657 61.7ACT CCA TCC AGA A AJ_P6 85653292 B07 AJ_499 /5AmMC6/CCC AAG TTT AAC CTC106534537 8687 59.3 ATG CTT TAG CGA A AJ_P6 85653293 B08 AJ_500/5AmMC6/CCC AAT TTG TAC GTT 106534538 8672 60.9 CCA ACC TAG GCA A AJ_P685653294 B09 AJ_501 /5AmMC6/CCC AAA TCG TTT GTT TCC 106534539 8727 59.8AGT AGG CAA A AJ_P6 85653295 B10 AJ_502 /5AmMC6/CCC AAG CAT CCT TGT CTT106586458 8672 60.7 AAC TGC AGA A AJ_P6 85653296 B11 AJ_503/5AmMC6/CCC AAA CTG GTA AGT 106534541 8697 62 CTT GGC TAC CCA A AJ_P685653297 B12 AJ_504 /5AmMC6/CCC AAG TCC ATG TGC 106534542 8675 63AAC ACC AAC TGA A AJ_P6 85653298 C01 AJ_505 /5AmMC6/CCC AAG TCA CAG GAC106534543 8675 61.7 TCC TCA ACA TGA A AJ_P6 85653299 C02 AJ_506/5AmMC6/CCC AAG TAC TCT CAT TCT 106577185 8672 60.1 GTG CAG ACA A AJ_P685653300 C03 AJ_507 /5AmMC6/CCC AAG GTT CCA CAC 106577186 8657 62.6TTT GTC ACG ACA A AJ_P6 85653301 C04 AJ_508 /5AmMC6/CCC AAA CTC GTC TGT106586459 8681 60.1 CCA TAA AGT CGA A AJ_P6 85653302 C05 AJ_509/5AmMC6/CCC AAC AAG GTG TGT 106577187 8712 60.6 TCT ACC ATT CGA A AJ_P685653303 C06 AJ_510 /5AmMC6/CCC AAA CTC GTG TTG 106577188 8736 58.6TAC TTA GAA CGA A AJ_P6 85653304 C07 AJ_511 /5AmMC6/CCC AAA GGC ATT GTC106534549 8723 59.9 AAC AAA CCA GTA A AJ_P6 85653305 C08 AJ_512/5AmMC6/CCC AAC AGT AGT TGT 106577189 8736 58.5 TAA CGA CTG CTA A AJ_P685653306 C09 AJ_513 /5AmMC6/CCC AAT GCT CAG GTC 106534551 8723 59.1AAA CAA ACT AGA A AJ_P6 85653307 C10 AJ_514 /5AmMC6/CCC AAT GTC GTA CTT106586460 8727 58.3 TGA GTA AGC CTA A AJ_P6 85653308 C11 AJ_515/5AmMC6/CCC AAG GCT AGA CGA 106534553 8739 60.2 ACA TTA CCA TGA A AJ_P685653309 C12 AJ_516 /5AmMC6/CCC AAC GAG TGT TCT 106586461 8752 60AGT GTT ACA CGA A AJ_P6 85653310 D01 AJ_517 /5AmMC6/CCC AAC AGG TTT ACG106534555 8752 60.3 TGT GTA CAG CTA A AJ_P6 85653311 D02 AJ_518/5AmMC6/CCC AAA GGT TCC TTC 106534556 8672 60.6 CAT GTA AGC TCA A AJ_P685653312 D03 AJ_519 /5AmMC6/CCC AAA GGC TTT GCT 106534557 8727 59.3GTT ACT TAG ACA A AJ_P6 85653313 D04 AJ_520 /5AmMC6/CCC AAC AAA GTA ACT106534558 8745 59.9 GTT CGT TGC GAA A AJ_P6 85653314 D05 AJ_521/5AmMC6/CCC AAA TGC TTG GAA 106534559 8696 59.1 CTT CTA ACT CGA A AJ_P685653315 D06 AJ_522 /5AmMC6/CCC AAC CTG AGT ACT 106534560 8721 60.4GTG CTC TGA AAA A AJ_P6 85653316 D07 AJ_523 /5AmMC6/CCC AAG GAC TCA AGT106534561 8657 61.6 CTT CCT TCA CGA A AJ_P6 85653317 D08 AJ_524/5AmMC6/CCC AAA GGG TTC CGT 106534562 8721 60.7 TCA CTA ACA TGA A AJ_P685653318 D09 AJ_525 /5AmMC6/CCC AAC CAG TAC TGC 106534563 8712 60.5ATT TCT TGG AGA A AJ_P6 85653319 D10 AJ_526 /5AmMC6/CCC AAC AAG CCT AGT106534564 8712 60.5 TCT GGT TGT ACA A AJ_P6 85653320 D11 AJ_527/5AmMC6/CCC AAC AGA CCT ACC 106534565 8672 60.5 TTT GTT GTA GCA A AJ_P685653321 D12 AJ_528 /5AmMC6/CCC AAG AAC CCT TCT 106534566 8681 60.9TTG ACT GCA AGA A AJ_P6 85653322 E01 AJ_529 /5AmMC6/CCC AAA GTC GTT TAG106534567 8672 60.2 TCC TCT GAC CAA A AJ_P6 85653323 E02 AJ_530/5AmMC6/CCC AAA GTC TCT TCG TTC 106534568 8712 60.2 AAC TGG AGA A AJ_P685653324 E03 AJ_531 /5AmMC6/CCC AAC GCA TTC TTA 106534569 8714 58.6ACA GAG ACA GTA A AJ_P6 85653325 E04 AJ_532 /5AmMC6/CCC AAC GAG TCT CTT106534570 8770 59.4 GAG AGG AAA CTA A AJ_P6 85653326 E05 AJ_533/5AmMC6/CCC AAC GTA GTG AGT 106534571 8755 61 AGA CGT ACA CCA A AJ_P685653327 E06 AJ_534 /5AmMC6/CCC AAA AAG CTT GTT 106534572 8696 59.6ACC TTC TGC AGA A AJ_P6 85653328 E07 AJ_535 /5AmMC6/CCC AAA CTT TGT ACT106534573 8745 59.1 GGA GTA GCC AAA A AJ_P6 85653329 E08 AJ_536/5AmMC6/CCC AAG CTT ACC TCT 106534574 8705 58.9 TAA GTG CAA GAA A AJ_P685653330 E09 AJ_537 /5AmMC6/CCC AAG AAC CTC TTA 106534575 8723 58.9AAG CTA AGC GAA A AJ_P6 85653331 E10 AJ_538 /5AmMC6/CCC AAG ACC TAA ACA106534576 8739 60.4 AGC TTG AGT CGA A AJ_P6 85653332 E11 AJ_539/5AmMC6/CCC AAT TTG CAT AGG 106534577 8687 59.5 TTC TTC CAA CGA A AJ_P685653333 E12 AJ_540 /5AmMC6/CCC AAG CAA GTT GCA 106534578 8672 61.1TTC CTC TCA TGA A AJ_P6 85653334 F01 AJ_541 /5AmMC6/CCC AAT CGG TAC ACG106534579 8739 59.9 ACA TAC ATG AGA A AJ_P6 85653335 F02 AJ_542/5AmMC6/CCC AAA CCT CTG TTT CTG 106534580 8712 60.2 AGT CGA AGA A AJ_P685653336 F03 AJ_543 /5AmMC6/CCC AAA CAC GTG TTG 106534581 8745 59.3GCT AGT CTA AAA A AJ_P6 85653337 F04 AJ_544 /5AmMC6/CCC AAC GGT TTA AGC106534582 8672 61.3 CTT TCA CCA TGA A AJ_P6 85653338 F05 AJ_545/5AmMC6/CCC AAC GGT TCA TGG 106534583 8786 61.7 ACT AAC TGA GGA A AJ_P685653339 F06 AJ_546 /5AmMC6/CCC AAA CCG TTC AGT 106534584 8721 61.4TTC ACA TGG GAA A AJ_P6 85653340 F07 AJ_547 /5AmMC6/CCC AAG ACC TCT CCA106534585 8657 61 CTT GAC TGT AGA A AJ_P6 85653341 F08 AJ_548/5AmMC6/CCC AAG TCT TTA CCT 106534586 8712 59.7 CAG TGT AGC AGA A AJ_P685653342 F09 AJ_549 /5AmMC6/CCC AAA CAG CTG AGT 106534587 8690 60.2CCT TCC ATA AGA A AJ_P6 85653343 F10 AJ_550 /5AmMC6/CCC AAA ACT GTC ATT106534588 8672 60.6 GCC TTC CTA GGA A AJ_P6 85653344 F11 AJ_551/5AmMC6/CCC AAG TCC ATT CAT 106534589 8712 60.6 TCG TTC GAA GGA A AJ_P685653345 F12 AJ_552 /5AmMC6/CCC AAG TCA CCT CTT 106534590 8737 61.6GGT AGT AAG GCA A AJ_P6 85653346 G01 AJ_553 /5AmMC6/CCC AAC CAT CAG CTT106534591 8712 60.9 TAG TTG GTG ACA A AJ_P6 85653347 G02 AJ_554/5AmMC6/CCC AAG TTA CCT GAC 106534592 8666 61.7 TCC ACT GGA CAA A AJ_P685653348 G03 AJ_555 /5AmMC6/CCC AAA GTT GGC ATC 106534593 8727 60.1TTT GTC GTC AAA A AJ_P6 85653349 G04 AJ_556/5AmMC6/CCC AAA CGT TGT GTC TTT 106534594 8687 59.4 AAC ATC CGA A AJ_P685653350 G05 AJ_557 /5AmMC6/CCC AAC AGT TTG GCT 106534595 8712 61.5TTG ACA TCA CGA A AJ_P6 85653351 G06 AJ_558 /5AmMC6/CCC AAA CGG TTT GCA106534596 8687 60.1 ACT CAT TCT TGA A AJ_P6 85653352 G07 AJ_559/5AmMC6/CCC AAG ACG ACT GTT 106534597 8672 59.8 TAC TTC CTC AGA A AJ_P685653353 G08 AJ_560 /5AmMC6/CCC AAG GAC TCC ATT 106534598 8657 61.9TCG ACT TCG ACA A AJ_P6 85653354 G09 AJ_561 /5AmMC6/CCC AAA TCA AGT CTA106534599 8763 58 GAC AGA AGG CTA A AJ_P6 85653355 G10 AJ_562/5AmMC6/CCC AAG TCG TCA TCA 106534600 8699 60.4 GCA AGA AAC CTA A AJ_P685653356 G11 AJ_563 /5AmMC6/CCC AAT CGT GTA CAT 106534601 8754 59.1GGA AAG CAC ATA A AJ_P6 85653357 G12 AJ_564 /5AmMC6/CCC AAC TTT GAA GCA106534602 8754 59.1 TGG AGA ACA CTA A AJ_P6 85653358 H01 AJ_565/5AmMC6/CCC AAA AGT CCT CTG 106534603 8727 58.6 TTT AGT TAG CGA A AJ_P685653359 H02 AJ_566 /5AmMC6/CCC AAG TAA CCA AAC 106534604 8699 60.5CAT GCT AGT CGA A AJ_P6 85653360 H03 AJ_567 /5AmMC6/CCC AAG GAC ATT GAC106534605 8675 62.4 TCA CCA TCA GCA A AJ_P6 85653361 H04 AJ_568/5AmMC6/CCC AAT GGG TAC TGC 106534606 8730 60 ATA CAC CAT AGA A AJ_P685653362 H05 AJ_569 /5AmMC6/CCC AAA GAA CTC GTC 106534607 8696 58.8TTC ATT TAC GGA A AJ_P6 85653363 H06 AJ_570 /5AmMC6/CCC AAA GGT CTT TGT106534608 8752 59.5 CCT AGT ACG AGA A AJ_P6 85653364 H07 AJ_571/5AmMC6/CCC AAC ATG GTT AAG 106534609 8770 60.3 GTC AAC TCG AGA A AJ_P685653365 H08 AJ_572 /5AmMC6/CCC AAG CTT GTA ACG 106534610 8672 59.9ACT TAC TCT CGA A AJ_P6 85653366 H09 AJ_573 /5AmMC6/CCC AAG ACC ACT CTC106534611 8657 61.7 CTA GCA TTT GGA A AJ_P6 85653367 H10 AJ_574/5AmMC6/CCC AAG TCC ATT CCC 106534612 8697 62.2 ATT GGT AGC AGA A AJ_P685653368 H11 AJ_575 /5AmMC6/CCC AAC ACT CTG TGT 106534613 8737 61.3CGT ACA TAG GGA A AJ_P6 85653369 H12 AJ_576 /5AmMC6/CCC AAA CTT GTG TGG106534614 8706 62.8 AAA CCG TAC CCA A AJ_P7 85653371 A01 AJ_577/5AmMC6/CCC AAA TGC CTT GGT 106534711 8761 61 GTC ATA CAG GAA A AJ_P785653372 A02 AJ_578 /5AmMC6/CCC AAT CGG AAG TCA 106534712 8763 57.8GAC TAG AAA CTA A AJ_P7 85653373 A03 AJ_579 /5AmMC6/CCC AAC CAG TAC CAG106534713 8755 61 AGG TGA AGT CTA A AJ_P7 85653374 A04 AJ_580/5AmMC6/CCC AAC ATA AAG GGA 106534714 8763 58.4 AAC TGA GCT CTA A AJ_P785653375 A05 AJ_581 /5AmMC6/CCC AAC TAA GAG GAG 106534715 8779 59.6AAC TCC AGT TGA A AJ_P7 85653376 A06 AJ_582 /5AmMC6/CCC AAC TAG GAA GTT106534716 8681 59.5 TAC TCC ACT CGA A AJ_P7 85653377 A07 AJ_583/5AmMC6/CCC AAC AAC GTC TGC 106534717 8730 60.3 TAA AGT AGG TCA A AJ_P785653378 A08 AJ_584 /5AmMC6/CCC AAC GTC ATC AAC 106534718 8714 58.4ATA GTA GGC TAA A AJ_P7 85653379 A09 AJ_585 /5AmMC6/CCC AAA TCG TCA CTA106534719 8763 57.3 GAG AGA GAA CTA A AJ_P7 85653380 A10 AJ_586/5AmMC6/CCC AAC TTG TCA CAT 106534720 8730 60 GAA GGA GAC CTA A AJ_P785653381 A11 AJ_587 /5AmMC6/CCC AAG GAG ACT CTA 106534721 8739 59.5GAA ACT TCC GAA A AJ_P7 85653382 A12 AJ_588 /5AmMC6/CCC AAG AGT TAC GCT106534722 8672 59.7 TCT ACT TCC AGA A AJ_P7 85653383 B01 AJ_589/5AmMC6/CCC AAA CCA GTC CTT 106534723 8746 61.5 AAG GGT AGG TCA A AJ_P785653384 B02 AJ_590 /5AmMC6/CCC AAA AGC CTA GAA 106534724 8723 58.8CAT TAC ATC GGA A AJ_P7 85653385 B03 AJ_591 /5AmMC6/CCC AAG CTG AAA GCA106534725 8690 61.1 CTC CAT CAT TGA A AJ_P7 85653386 B04 AJ_592/5AmMC6/CCC AAT CAG TGT GAC 106534726 8657 61.1 TCC ATC CCT AGA A AJ_P785653387 B05 AJ_593 /5AmMC6/CCC AAG CTA CTT AAC 106534727 8687 58.6TCT GTT TCG GAA A AJ_P7 85653388 B06 AJ_594 /5AmMC6/CCC AAA TGC TTT CAC106534728 8752 60.6 TGG TCT AGG GAA A AJ_P7 85653389 B07 AJ_595/5AmMC6/CCC AAC AGT TGT TCG 106534729 8712 60.9 TTC ATG ACC AGA A AJ_P785653390 B08 AJ_596 /5AmMC6/CCC AAT CAC GAA ACG 106534730 8739 59.8ACT ACT TAG GGA A AJ_P7 85653391 B09 AJ_597/5AmMC6/CCC AAC ATT GTT TGG TTC 106534731 8727 60.1 ATC AAG CGA A AJ_P785653392 B10 AJ_598 /5AmMC6/CCC AAA TTC TTG TGG 106534732 8736 59.8TAC AAC ATG CGA A AJ_P7 85653393 B11 AJ_599 /5AmMC6/CCC AAC CTG ACC AAC106534733 8672 61 GGT TCA TTT GTA A AJ_P7 85653394 B12 AJ_600/5AmMC6/CCC AAG ACC ATT ACG 106534734 8672 60.8 TCT TGC CTT GAA A AJ_P785653395 C01 AJ_601 /5AmMC6/CCC AAG CCA TAC CTC 106534735 8672 60.8ATT GAG CTT TGA A AJ_P7 85653396 C02 AJ_602 /5AmMC6/CCC AAA GGA CTC TTC106534736 8657 61.7 CGT AAC CTG TCA A AJ_P7 85653397 C03 AJ_603/5AmMC6/CCC AAG GAG TGC ATT 106534737 8761 60.8 TCG TAA CCT GAA A AJ_P785653398 C04 AJ_604 /5AmMC6/CCC AAT CAC AAG CGA 106534738 8754 58.6AAG TAG TGT CTA A AJ_P7 85653399 C05 AJ_605 /5AmMC6/CCC AAT CGA AGA GAC106534739 8770 60.1 GAC TTG AGT TCA A AJ_P7 85653400 C06 AJ_606/5AmMC6/CCC AAA TGG CTT TGG 106534740 8761 61.2 TAC AAC TGA CGA A AJ_P785653401 C07 AJ_607 /5AmMC6/CCC AAG AGA CGT TGG 106534741 8755 61.6AAC ACC TAC TGA A AJ_P7 85653402 C08 AJ_608 /5AmMC6/CCC AAG AAA GCT GTT106534742 8699 61.1 CAA ACC TCA CGA A AJ_P7 85653403 C09 AJ_609/5AmMC6/CCC AAG TGA GTC TTC 106534743 8761 60.4 GAA ACT TCG GAA A AJ_P785653404 C10 AJ_610 /5AmMC6/CCC AAC CAG TGT TAA 106534744 8786 62.4CGG AAC TTG GGA A AJ_P7 85653405 C11 AJ_611 /5AmMC6/CCC AAC AGG TGT ACT106534745 8777 61.3 TGG TAC TAC GGA A AJ_P7 85653406 C12 AJ_612/5AmMC6/CCC AAG TAC CAT CCT 106534746 8672 59.8 TAC GTA GCT TGA A AJ_P785653407 D01 AJ_613 /5AmMC6/CCC AAG CTA CTT CCA 106534747 8706 60.9CTA GGT ACA GGA A AJ_P7 85653408 D02 AJ_614 /5AmMC6/CCC AAG TAC CTC AAC106534748 8699 60.1 AAG TCA AGG CTA A AJ_P7 85653409 D03 AJ_615/5AmMC6/CCC AAG TAC CCA AGA 106534749 8739 59.8 GAC TAA GCT TGA A AJ_P785653410 D04 AJ_616 /5AmMC6/CCC AAT GAA CCA AAC 106534750 8699 61ACT GAC CTG TGA A AJ_P7 85653411 D05 AJ_617 /5AmMC6/CCC AAG TGC ACA TCG106534751 8699 60.8 AAC CAA CTT AGA A AJ_P7 85653412 D06 AJ_618/5AmMC6/CCC AAT GCT TAG CGT 106534752 8696 58.2 ACT ACC ATT AGA A AJ_P785653413 D07 AJ_619 /5AmMC6/CCC AAG TTT GAC GTT 106534753 8681 61.2CAA CCA TCA CGA A AJ_P7 85653414 D08 AJ_620 /5AmMC6/CCC AAT TTA GCT TGT106534754 8712 60.2 CCA CTC AGA GGA A AJ_P7 85653415 D09 AJ_621/5AmMC6/CCC AAC GCT ACT TTC TTA 106534755 8687 58.4 GTT AGA GCA A AJ_P785653416 D10 AJ_622 /5AmMC6/CCC AAA AGC CTT TCC 106534756 8672 60.9ACT GTT ACT GGA A AJ_P7 85653417 D11 AJ_623 /5AmMC6/CCC AAC CTG TTA CCT106534757 8697 61.9 CAG ACA TTG GGA A AJ_P7 85653418 D12 AJ_624/5AmMC6/CCC AAC GTC ATT TAG 106534758 8752 59.6 GTC TCT AAG GGA A AJ_P785653419 E01 AJ_625 /5AmMC6/CCC AAA CGT CTT GGG 106534759 8712 60.2TTA CAC TAC TGA A AJ_P7 85653420 E02 AJ_626 /5AmMC6/CCC AAT CAC AGA ACC106534760 8690 60.8 AGT CAG CTT TGA A AJ_P7 85653421 E03 AJ_627/5AmMC6/CCC AAG TGG TAC TCT 106534761 8697 60.9 CGT AAC TCC AGA A AJ_P785653422 E04 AJ_628 /5AmMC6/CCC AAG AAC TCC TAC 106534762 8675 61.2CAA GAC TCG TGA A AJ_P7 85653423 E05 AJ_629 /5AmMC6/CCC AAT TTG ACT TGA106534763 8705 59.7 ACG CAT AAC CGA A AJ_P7 85653424 E06 AJ_630/5AmMC6/CCC AAT TGA GAC CTC 106534764 8699 59.8 ACG AGA ACA CTA A AJ_P785653425 E07 AJ_631 /5AmMC6/CCC AAA CAA AGT CAT 106534765 8745 59.8TGG GTT CGC TAA A AJ_P7 85653426 E08 AJ_632 /5AmMC6/CCC AAT CGA ACA AAC106534766 8699 60.4 CTA GAG TGC TCA A AJ_P7 85653427 E09 AJ_633/5AmMC6/CCC AAG GTC TTA GCT 106534767 8681 59.8 ACA ACC TCA TGA A AJ_P785653428 E10 AJ_634 /5AmMC6/CCC AAG CTT TGA AGC 106534768 8681 60.7CTT CCA ACT AGA A AJ_P7 85653429 E11 AJ_635 /5AmMC6/CCC AAT ACA GGT GTC106534769 8699 60.5 ACA AAC TCA CGA A AJ_P7 85653430 E12 AJ_636/5AmMC6/CCC AAC CGT TCA TAA 106534770 8699 60.4 CAA GGG AAC CTA A AJ_P785653431 F01 AJ 637 /5AmMC6/CCC AAA GTA CCC AAA 106534771 8739 61GCA TGT CTG GAA A AJ_P7 85653432 F02 AJ_638/5AmMC6/CCC AAA TGT TCT CTT TAC 106534772 8727 58.8 GCT AGG GAA A AJ_P785653433 F03 AJ_639 /5AmMC6/CCC AAT TTG ACT TCA 106534773 8745 59.3GAC GAA AGC TGA A AJ_P7 85653434 F04 AJ_640 /5AmMC6/CCC AAT ACA GAA ACG106534774 8723 59 ACA TAC GCT TGA A AJ_P7 85653435 F05 AJ_641/5AmMC6/CCC AAT CAC CAG AAG 106534775 8699 60 AAC TAC CTG TGA A AJ_P785653436 F06 AJ_642 /5AmMC6/CCC AAT ACG AAC GAC 106534776 8770 60.2AGG TCA TGG TTA A AJ_P7 85653437 F07 AJ_643 /5AmMC6/CCC AAG AAC TCC AAC106534777 8690 59.9 CAT GTA GTC GTA A AJ_P7 85653438 F08 AJ_644/5AmMC6/CCC AAA TTG CGT TCT 106534778 8696 59.6 TCA GTA CAC GAA A AJ_P785653439 F09 AJ_645 /5AmMC6/CCC AAA TCT GCT TCC TGT 106534779 8672 60AGT ACA CGA A AJ_P7 85653440 F10 AJ_646 /5AmMC6/CCC AAG GTC ACT TGC106534780 8675 62.3 AAC CTA GAA CCA A AJ_P7 85653441 F11 AJ_647/5AmMC6/CCC AAG GCT TAG TAC 106534781 8715 61.5 GAC AGT AAC CCA A AJ_P785653442 F12 AJ_648 /5AmMC6/CCC AAC AAG TGA AGT 106534782 8795 62GGT CTG ACC AGA A AJ_P7 85653443 G01 AJ_649 /5AmMC6/CCC AAC AGA GTA GTG106534783 8770 59.3 TGA CTA GCC TAA A AJ_P7 85653444 G02 AJ_650/5AmMC6/CCC AAT CAC AAG GAG 106534784 8754 59.1 TAG CAA CTT TGA A AJ_P785653445 G03 AJ_651 /5AmMC6/CCC AAC CTG TAA GTG 106534785 8779 60.5AAA CGA CTG GAA A AJ_P7 85653446 G04 AJ_652 /5AmMC6/CCC AAC CCT AGT TGA106534786 8755 61.8 GGA CAA ACT GGA A AJ_P7 85653447 G05 AJ_653/5AmMC6/CCC AAG GCA TCA CAC 106534787 8690 60.8 CTA GCA AGT TTA A AJ_P785653448 G06 AJ_654 /5AmMC6/CCC AAG ACC TAC CCT 106534788 8666 60.9ACA GAG CTT GTA A AJ_P7 85653449 G07 AJ_655 /5AmMC6/CCC AAT TTC GTA ACA106534789 8736 59.1 AGT TGG ACT CGA A AJ_P7 85653450 G08 AJ_656/5AmMC6/CCC AAT CAA AGA AAC 106534790 8763 59.8 AGG TTG CAC TGA A AJ_P785653451 G09 AJ_657 /5AmMC6/CCC AAC GTC TTA GAG 106534791 8657 61.7TCC TTG AAC CCA A AJ_P7 85653452 G10 AJ_658 /5AmMC6/CCC AAT GCT GAA ACG106534792 8687 59.8 TTT CCC TTG TAA A AJ_P7 85653453 G11 AJ_659/5AmMC6/CCC AAC AGG TTT GTT 106534793 8752 60.8 TGA CTC AGA CGA A AJ_P785653454 G12 AJ_660 /5AmMC6/CCC AAC CTT CGA CAT 106534794 8723 59AAA GAA AGC GTA A AJ_P7 85653455 H01 AJ_661 /5AmMC6/CCC AAT GAA CCA TTA106534795 8763 59.4 GCA AGC AAG GTA A AJ_P7 85653456 H02 AJ_662/5AmMC6/CCC AAT GAA CCT TGA 106534796 8739 61.3 GCA CAA ACT GGA A AJ_P785653457 H03 AJ_663 /5AmMC6/CCC AAA GGG TTC TTG 106534797 8737 61.8GAC AGT ACC TCA A AJ_P7 85653458 H04 AJ_664 /5AmMC6/CCC AAC TGT AAA GGA106534798 8721 59.5 GTT CGT ACC CTA A AJ_P7 85653459 H05 AJ_665/5AmMC6/CCC AAT CGA GAA GGA 106534799 8779 59.8 AGT CAC ACT GTA A AJ_P785653460 H06 AJ_666 /5AmMC6/CCC AAC TAA AGG AAG 106534800 8770 60.4TGT CAG CTG TCA A AJ_P7 85653461 H07 AJ_667 /5AmMC6/CCC AAG CAC ATA AGG106534801 8779 61.1 TCA AAC GTG TGA A AJ_P7 85653462 H08 AJ_668/5AmMC6/CCC AAC GTT GAA GGA 106534802 8779 61 ACA TTC ACA GGA A AJ_P785653463 H09 AJ_669 /5AmMC6/CCC AAT GTG AGC TGA 106534803 8763 59.8CAA ACA ACA TGA A AJ_P7 85653464 H10 AJ_670 /5AmMC6/CCC AAG CTA CTC TAA106534804 8675 61.4 CAC GAC TGG ACA A AJ_P7 85653465 H11 AJ_671/5AmMC6/CCC AAG CCT AAC CTT 106534805 8681 60.8 CAA GTG CAT GTA A AJ_P785653466 H12 AJ_672 /5AmMC6/CCC AAG TAA ACA CCT 106534806 8730 59.9CTA GGT TCG GAA A AJ_P8 85653468 A01 AJ_673 /5AmMC6/CCC AAG TCT TGA CTC106534807 8681 60 TCG ACT CGA AAA A AJ_P8 85653469 A02 AJ_674/5AmMC6/CCC AAC TGC AGA GTG 106534808 8779 61.1 GAC TTG ACA AAA A AJ_P885653470 A03 AJ_675 /5AmMC6/CCC AAC AGC TCT GGT 106534809 8721 60GTA CTT AAG ACA A AJ_P8 85653471 A04 AJ_676 /5AmMC6/CCC AAT ACG AGA GAG106534810 8779 59.6 ACG TTT ACG ACA A AJ_P8 85653472 A05 AJ_677/5AmMC6/CCC AAG TAC CCT ACT 106534811 8666 60.9 CTC GTC AAG GAA A AJ_P885653473 A06 AJ_678 /5AmMC6/CCC AAT AAC GAC ACA 106534812 8699 60.5ACT GGT TAC CGA A AJ_P8 85653474 A07 AJ_679 /5AmMC6/CCC AAC ACG TCA TAA106534813 8675 61.5 CGG TAG ACC TCA A AJ_P8 85653475 A08 AJ_680/5AmMC6/CCC AAT CCC AAG CAA 106534814 8699 60.2 CAG TCA GTA GTA A AJ_P885653476 A09 AJ_681 /5AmMC6/CCC AAT AAA CGA ACA 106534815 8699 60.8CCT GTG AGC TCA A AJ_P8 85653477 A10 AJ_682 /5AmMC6/CCC AAG TTA CCA GAC106534816 8699 60.2 TCA ACA ACG GTA A AJ_P8 85653478 A11 AJ_683/5AmMC6/CCC AAG TTA GCT TGA 106534817 8690 60.8 CCA ACC AAC GTA A AJ_P885653479 A12 AJ_684 /5AmMC6/CCC AAG ACC ATC ACT 106534818 8675 60.7ACA GGA GTC CTA A AJ_P8 85653480 B01 AJ_685/5AmMC6/CCC AAG TAC TCT TCT TAC 106534819 8712 59.3 GGT AGC AGA A AJ_P885653481 B02 AJ_686 /5AmMC6/CCC AAT TTG CCA TCG 106534820 8714 60.4ACA ACG TGA AAA A AJ_P8 85653482 B03 AJ_687 /5AmMC6/CCC AAA GTC TCT TGG106534821 8752 60.2 GTA CAA CGT GTA A AJ_P8 85653483 B04 AJ_688/5AmMC6/CCC AAT GAC CTT CTC GTT 106534822 8672 60.2 ACA ACG GTA A AJ_P885653484 B05 AJ_689 /5AmMC6/CCC AAT ACC GTT CTG 106534823 8736 58.6TTA AGA AGC GTA A AJ_P8 85653485 B06 AJ_690 /5AmMC6/CCC AAA GTC CTT CCT106534824 8672 59.6 CTA GTT ACG GAA A AJ_P8 85653486 B07 AJ_691/5AmMC6/CCC AAG CCA TAC AAC 106534825 8730 60.6 ATT GGA CTG GTA A AJ_P885653487 B08 AJ_692 /5AmMC6/CCC AAC CTG AGA GGT 106534826 8761 59.8AAG CTT GAC TTA A AJ_P8 85653488 B09 AJ_693 /5AmMC6/CCC AAC ACC TAG TAG106534827 8746 61.2 TCG TTG GAC AGA A AJ_P8 85653489 B10 AJ_694/5AmMC6/CCC AAG TAC ACT AAA 106534828 8723 59.6 CCG TTG CGA AAA A AJ_P885653490 B11 AJ_695 /5AmMC6/CCC AAC CAC TGG TAC 106534829 8730 60.8GGA AAG CTT TAA A AJ_P8 85653491 B12 AJ_696 /5AmMC6/CCC AAG ACC ACT CTT106534830 8746 61.2 TGA GGA GTA CGA A AJ_P8 85653492 C01 AJ_697/5AmMC6/CCC AAG ACT GAC CTT 106534831 8795 62 GGA AAG TAG GCA A AJ_P885653493 C02 AJ_698 /5AmMC6/CCC AAC TCA CGT TAC 106534832 8739 60GAA ACA GAG GTA A AJ_P8 85653494 C03 AJ_699 /5AmMC6/CCC AAG CGT AAC GTC106534833 8687 59.2 ATT TAC TTT CGA A AJ_P8 85653495 C04 AJ_700/5AmMC6/CCC AAC GAA CGT GTC 106534834 8687 59.7 ATT TCA CTT TGA A AJ_P885653496 C05 AJ_701 /5AmMC6/CCC AAA TCT CTG GTG 106534835 8657 62.1TCC ATC CGA ACA A AJ_P8 85653497 C06 AJ_702 /5AmMC6/CCC AAA GCT TTG GAG106534836 8761 61.1 TCT GTG ACA ACA A AJ_P8 85653498 C07 AJ_703/5AmMC6/CCC AAG GGT ACT AGG 106534837 8786 61.9 CTT GTG ACA ACA A AJ_P885653499 C08 AJ_704 /5AmMC6/CCC AAT AGC GAA CAC 106534838 8699 60CTA GTT ACG ACA A AJ_P8 85653500 C09 AJ_705 /5AmMC6/CCC AAT CAC GAG TCC106534839 8675 61.7 AAG AGT TAC CCA A AJ_P8 85653501 C10 AJ_706/5AmMC6/CCC AAT GAG AAC AAA 106534840 8763 59.1 GGC TAA CCG TTA A AJ_P885653502 C11 AJ_707 /5AmMC6/CCC AAC TCG TCA TAG 106534841 8699 59.9AAC ACC AAG GTA A AJ_P8 85653503 C12 AJ_708 /5AmMC6/CCC AAC TCC ATG CAA106534842 8723 59 GTA AAG AAC GTA A AJ_P8 85653504 D01 AJ_709/5AmMC6/CCC AAA TGT GAC TAC 106534843 8705 59.3 CGA AAC GCT TTA A AJ_P885653505 D02 AJ_710 /5AmMC6/CCC AAG ACA AGT TGA 106534844 8699 60.8CCA ACG CAT CTA A AJ_P8 85653506 D03 AJ_711 /5AmMC6/CCC AAC TGC ACA GTT106534845 8690 60.5 TAC AAC CTA GGA A AJ_P8 85653507 D04 AJ_712/5AmMC6/CCC AAG CTG ACT GTC 106534846 8672 59.8 TTA ACC CTT AGA A AJ_P885653508 D05 AJ_713 /5AmMC6/CCC AAG GTC AAG TCG 106534847 8739 60ACA AGC TAA CTA A AJ_P8 85653509 D06 AJ_714 /5AmMC6/CCC AAC ACG TGA GTT106534848 8675 62 CCA ACC CTA AGA A AJ_P8 85653510 D07 AJ_715/5AmMC6/CCC AAG CCA TAA CCA 106534849 8690 59.9 TCA GTC TGA GTA A AJ_P885653511 D08 AJ_716 /5AmMC6/CCC AAG TCA ACA CAC 106534850 8699 60TCA GCA GTA GTA A AJ_P8 85653512 D09 AJ_717 /5AmMC6/CCC AAG TAC CTA CTC106534851 8672 60 ATG CTT GCA GTA A AJ_P8 85653513 D10 AJ_718/5AmMC6/CCC AAA TGT ACG TAA 106534852 8723 59.2 AGC ACA AGC CTA A AJ_P885653514 D11 AJ_719 /5AmMC6/CCC AAC GTG TAA AGG 106534853 8779 60AAC TAG GCT ACA A AJ_P8 85653515 D12 AJ_720 /5AmMC6/CCC AAG GTC ACT AAC106534854 8675 61.4 TCA GGA ACT CCA A AJ_P8 85653516 E01 AJ_721/5AmMC6/CCC AAT TCG AAG TAA 106534855 8723 59.4 GCA ACA CCA TGA A AJ_P885653517 E02 AJ_722 /5AmMC6/CCC AAT CGG AAG TGT 106534856 8779 60.6AAA CTG GAC ACA A AJ_P8 85653518 E03 AJ_723 /5AmMC6/CCC AAG ACT CAC AAA106534857 8690 60.2 CCG TAC TTG GTA A AJ_P8 85653519 E04 AJ_724/5AmMC6/CCC AAC ATT CTG CAT 106534858 8770 60.2 AGG AGA CAG TGA A AJ_P885653520 E05 AJ_725 /5AmMC6/CCC AAA CCC ATG CAC 106534859 8699 61.3ATT GAG AAC TGA A AJ_P8 85653521 E06 AJ_726 /5AmMC6/CCC AAT GGT CAG GAC106534860 8739 59.7 TAA ACT ACC AGA A AJ_P8 85653522 E07 AJ_727/5AmMC6/CCC AAG CTT CCA GAA 106534861 8712 60.6 CTT TAC TTG GGA A AJ_P885653523 E08 AJ_728 /5AmMC6/CCC AAG TTC AAC TCC 106534862 8675 62.3AAC GTC AGG ACA A AJ_P8 85653524 E09 AJ_729 /5AmMC6/CCC AAG TTA CTA CCA106534863 8681 59.4 TAC GAC TCG TGA A AJ_P8 85653525 E10 AJ_730/5AmMC6/CCC AAC AGA CAT GCA 106534864 8699 60.5 CTT AAC TCA GGA A AJ_P885653526 E11 AJ_731 /5AmMC6/CCC AAC TTG AAC CTA 106534865 8779 60.2GAA AGG GTA GCA A AJ_P8 85653527 E12 AJ_732 /5AmMC6/CCC AAG TCC TAC CTT106534866 8730 58.8 AAG AGA CGA GTA A AJ_P8 85653528 F01 AJ_733/5AmMC6/CCC AAC AGT TAG GGA 106534867 8761 61.1 AGC TTT GCA TCA A AJ_P885653529 F02 AJ_734 /5AmMC6/CCC AAC GTC TAG CTA 106534868 8745 58.2GAA GAA GTT TCA A AJ_P8 85653530 F03 AJ_735/5AmMC6/CCC AAT TTA GTC ACC TCT 106534869 8672 60 GGA ACC GTA A AJ_P885653531 F04 AJ_736 /5AmMC6/CCC AAC AGT GAA GGA 106534870 8730 60.9ACC TTT CGT CAA A AJ_P8 85653532 F05 AJ_737 /5AmMC6/CCC AAA GGC TTC CTT106534871 8687 59.1 TCA GAC AGT TTA A AJ_P8 85653533 F06 AJ_738/5AmMC6/CCC AAA CGG TTG TTG 106534872 8761 60.9 AGT CGA ACC ATA A AJ_P885653534 F07 AJ_739 /5AmMC6/CCC AAA CCT CTG AGT 106534873 8730 60.5TGG CTA AAC AGA A AJ_P8 85653535 F08 AJ_740 /5AmMC6/CCC AAG CAG TTG TAA106534874 8779 60.3 GAC CAA GAC GTA A AJ_P8 85653536 F09 AJ_741/5AmMC6/CCC AAG AGA GCT ACC 106534875 8727 58.6 GTT TCT TTG TAA A AJ_P885653537 F10 AJ_742 /5AmMC6/CCC AAA GGG TTC TCC 106534876 8761 60.4AAG TTT ACA GGA A AJ_P8 85653538 F11 AJ_743 /5AmMC6/CCC AAC GTT AGT GTG106534877 8727 59.6 TTC AAG CTT CAA A AJ_P8 85653539 F12 AJ_744/5AmMC6/CCC AAC TCA CTG CAA 106534878 8739 60.8 AGG TAA AGG TCA A AJ_P885653540 G01 AJ_745 /5AmMC6/CCC AAG AGC TCA CAA 106534879 8786 61.9GGT GTT AGG TCA A AJ_P8 85653541 G02 AJ_746 /5AmMC6/CCC AAC TGT CTA CTG106534880 8752 60.4 AAG GAG TTT GCA A AJ_P8 85653542 G03 AJ_747/5AmMC6/CCC AAA GCT TCC TTT ACT 106534881 8687 58.3 GAC TAG TGA A AJ_P885653543 G04 AJ_748 /5AmMC6/CCC AAC TGC TAC CCT 106534882 8681 60.1TGA GTA AAG TCA A AJ_P8 85653544 G05 AJ_749 /5AmMC6/CCC AAG CTC ATT CCC106534883 8681 60.2 TTG AAC AGA GTA A AJ_P8 85653545 G06 AJ_750/5AmMC6/CCC AAG AGA CTG TGC 106534884 8715 61.9 ACA ACC CTT AGA A AJ_P885653546 G07 AJ_751 /5AmMC6/CCC AAC GGT TAA CCT 106534885 8714 59.4CAA GTG CTA AAA A AJ_P8 85653547 G08 AJ_752 /5AmMC6/CCC AAA CCC TTG GGT106534886 8755 61.7 AAG CTA GAG ACA A AJ_P8 85653548 G09 AJ_753/5AmMC6/CCC AAA TTG CTC ACG 106534887 8672 61.2 TTC TCA TGG ACA A AJ_P885653549 G10 AJ_754 /5AmMC6/CCC AAC CCT AGG AAG 106534888 8690 60.3CCA TCA GTT TAA A AJ_P8 85653550 G11 AJ_755 /5AmMC6/CCC AAA CCG TTT GAA106534889 8672 61.3 CCT TCT GGT CAA A AJ_P8 85653551 G12 AJ_756/5AmMC6/CCC AAT CCG AAG GAG 106534890 8739 60.7 AAC TTT GAC CAA A AJ_P885653552 H01 AJ_757 /5AmMC6/CCC AAT TGA GTC TGA 106534891 8754 59.1AGC AAC CAA GTA A AJ_P8 85653553 H02 AJ_758 /5AmMC6/CCC AAC TGT TTA GAG106534892 8727 58.7 TGA CAT TGC CTA A AJ_P8 85653554 H03 AJ_759/5AmMC6/CCC AAT ACT GTT AAG 106534893 8705 58.5 GCT ACA ACG CTA A AJ_P885653555 H04 AJ_760 /5AmMC6/CCC AAA TCG GTT CGT 106534894 8672 60.1TCA CTA CTC AGA A AJ_P8 85653556 H05 AJ_761 /5AmMC6/CCC AAC CAA GGT TGG106534895 8737 62 CTT AGT AGT CCA A AJ_P8 85653557 H06 AJ_762/5AmMC6/CCC AAG GCT ACA GAC 106534896 8672 60.6 TTT CCC ATT TGA A AJ_P885653558 H07 AJ_763 /5AmMC6/CCC AAG AAC CTC ACG 106534897 8712 61TGT GCT TGT TAA A AJ_P8 85653559 H08 AJ_764 /5AmMC6/CCC AAG ACA TCC ACT106534898 8672 60.5 CTT GTT TGA CGA A AJ_P8 85653560 H09 AJ_765/5AmMC6/CCC AAG GTA CAC ACC 106534899 8657 62.2 TTT GCC TTA CGA A AJ_P885653561 H10 AJ_766 /5AmMC6/CCC AAC GAG TTG GAG 106534900 8779 60.1TAA CAT ACG ACA A AJ_P8 85653562 H11 AJ_767 /5AmMC6/CCC AAA CGG TTG TGG106534901 8761 60.3 TAA CAT CCT AGA A AJ_P8 85653563 H12 AJ_768/5AmMC6/CCC AAG ACC TTG ACT 106586462 8795 61.7 GGA GAA ACG GTA A AJ_P985653565 A01 AJ_769 /5AmMC6/CCC AAG CTC ACT ACC 106534903 8672 60.6ATT GTC ATT GGA A AJ_P9 85653566 A02 AJ_770 /5AmMC6/CCC AAT CCG TTA CGT106534904 8770 60.6 GAA GGG TAA ACA A AJ_P9 85653567 A03 AJ_771/5AmMC6/CCC AAT ACA GAC TGC 106534905 8699 60.1 ACA CTC AGG TAA A AJ_P985653568 A04 AJ_772 /5AmMC6/CCC AAT TTA CGT AGT 106534906 8696 59.3CCA ACT TGC GAA A AJ_P9 85653569 A05 AJ_773 /5AmMC6/CCC AAG ACC TTA CTA106534907 8690 59.4 CCT GAA GCA GTA A AJ_P9 85653570 A06 AJ_774/5AmMC6/CCC AAC ATT GTT TCT CTG 106534908 8687 59.4 ACA AGC TGA A AJ_P985653571 A07 AJ_775 /5AmMC6/CCC AAC AGC AGT TTA 106534909 8739 61GCC AAG AAG TCA A AJ_P9 85653572 A08 AJ_776 /5AmMC6/CCC AAG ACC TTG GAC106534910 8657 60.9 TCT CTC TAA CGA A AJ_P9 85653573 A09 AJ_777/5AmMC6/CCC AAG TAC TTT CTT CCA 106534911 8672 60.1 GTC AGA GCA A AJ_P985653574 A10 AJ_778 /5AmMC6/CCC AAT CAG ACA ACC 106534912 8681 60.7TTG TTC ATC GGA A AJ_P9 85653575 A11 AJ_779 /5AmMC6/CCC AAT CAC CTG TTG106534913 8712 60.7 CAT TCA TAG GGA A AJ_P9 85653576 A12 AJ_780/5AmMC6/CCC AAT TTG CAG TGA 106534914 8714 59.8 ACA CCA ACA GTA A AJ_P985653577 B01 AJ_781 /5AmMC6/CCC AAG TCT GCA GTA 106534915 8699 60.4ACA CAC CAA GTA A AJ_P9 85653578 B02 AJ_782 /5AmMC6/CCC AAT GTC TCA GTC106534916 8672 59.7 TCC ACA TTA GGA A AJ_P9 85653579 B03 AJ_783/5AmMC6/CCC AAG TAC ACC ATT 106534917 8672 61.2 TCG CAT TTC GGA A AJ_P985653580 B04 AJ_784 /5AmMC6/CCC AAG CTA CCA CTT 106534918 8730 60TAG AAG TAG GCA A AJ_P9 85653581 B05 AJ_785 /5AmMC6/CCC AAT CAC AAG GTT106534919 8739 60 ACC ACA GGA GTA A AJ_P9 85653582 B06 AJ_786/5AmMC6/CCC AAC ACC ATG GAC 106534920 8715 61.9 ACT TCT AAG GGA A AJ_P985653583 B07 AJ_787 /5AmMC6/CCC AAC CTG AAA GAG 106534921 8736 59.3TTT CTT GCG TAA A AJ_P9 85653584 B08 AJ_788 /5AmMC6/CCC AAG AGA CGT GTC106534922 8706 61.3 ATC TCA TCC AGA A AJ_P9 85653585 B09 AJ_789/5AmMC6/CCC AAT AGC GTA GAC 106534923 8723 59.2 AAC TTC AAA GCA A AJ_P985653586 B10 AJ_790 /5AmMC6/CCC AAA GTT CTC TCG TTC 106534924 8687 58.6ATA GCT GAA A AJ_P9 85653587 B11 AJ_791 /5AmMC6/CCC AAA TTG GTC TTC106534925 8736 59.7 TGC ATA AAG CGA A AJ_P9 85653588 B12 AJ_792/5AmMC6/CCC AAT CGA AGG AGT 106534926 8761 58.8 AGT CTA CCT GTA A AJ_P985653589 C01 AJ_793 /5AmMC6/CCC AAT CAG GAC TAC 106534927 8715 61.8GGA AAG TTC CCA A AJ_P9 85653590 C02 AJ_794 /5AmMC6/CCC AAC CGT AAC ATC106534928 8675 62 CAT GAG ACG TCA A AJ_P9 85653591 C03 AJ_795/5AmMC6/CCC AAT GCG AAA GAG 106534929 8770 60.8 GTA CCG TTT ACA A AJ_P985653592 C04 AJ_796 /5AmMC6/CCC AAG ACA CAT CCA 106534930 8675 62.1ACT GGT GAC TCA A AJ_P9 85653593 C05 AJ_797 /5AmMC6/CCC AAG ACC ATC CTT106534931 8675 61.7 CAA GAG ACG TCA A AJ_P9 85653594 C06 AJ_798/5AmMC6/CCC AAG CTC TCA AGT 106534932 8690 60.6 CTA AAC AGT GCA A AJ_P985653595 C07 AJ_799 /5AmMC6/CCC AAC AAA GTA GAA 106534933 8763 58.6ACT CGT AGC TGA A AJ_P9 85653596 C08 AJ_800 /5AmMC6/CCC AAC CAG AGT GTG106534934 8795 61.3 AAC ACT AGG GTA A AJ_P9 85653597 C09 AJ_801/5AmMC6/CCC AAC CTC ATG AAG 106534935 8715 61.5 ACT CCA AGG GTA A AJ_P985653598 C10 AJ_802 /5AmMC6/CCC AAA CCT GTG GAC 106534936 8666 62.1ACT ACA CCT TGA A AJ_P9 85653599 C11 AJ_803 /5AmMC6/CCC AAA GTT CAG AGT106534937 8672 59.9 TCT CTC CAC TGA A AJ_P9 85653600 C12 AJ_804/5AmMC6/CCC AAG CTA CTT TCA 106534938 8721 60.4 ACT GAC AGT GGA A AJ_P985653601 D01 AJ_805 /5AmMC6/CCC AAG CCA TCT TCT 106534939 8681 60.1ACT GAA CGG TAA A AJ_P9 85653602 D02 AJ_806 /5AmMC6/CCC AAT GTT TCA GTC106534940 8687 59.4 CAT TGA ACG CTA A AJ_P9 85653603 D03 AJ_807/5AmMC6/CCC AAA TTG CTT CTC 106534941 8687 59.1 ACG TCA TTA GGA A AJ_P985653604 D04 AJ_808 /5AmMC6/CCC AAT GGG AAC TCT 106534942 8739 60.8GAA ACA TCC GAA A AJ_P9 85653605 D05 AJ_809 /5AmMC6/CCC AAT CGT AGA GTC106534943 8723 58.4 AAA CCA CAA GTA A AJ_P9 85653606 D06 AJ_810/5AmMC6/CCC AAC AGG TGT CGT 106534944 8786 62.5 GTG AAA CAG TCA A AJ_P985653607 D07 AJ_811 /5AmMC6/CCC AAG GTC ATT AAG 106534945 8657 62CCT TCG ACT CCA A AJ_P9 85653608 D08 AJ_812 /5AmMC6/CCC AAC TTG AAG TGA106534946 8779 61.3 AGG CAA CCA TGA A AJ_P9 85653609 D09 AJ_813/5AmMC6/CCC AAC AAC TAG GAG 106534947 8761 60.1 TGC TCT GGT TAA A AJ_P985653610 D10 AJ_814 /5AmMC6/CCC AAG ACC ATA GCA 106534948 8675 61.9TCC AAG TCG TCA A AJ_P9 85653611 D11 AJ_815 /5AmMC6/CCC AAT CGA GAA ACA106534949 8723 58.4 CCT GTA CAA GTA A AJ_P9 85653612 D12 AJ_816/5AmMC6/CCC AAC AGT CTT TAA 106534950 8754 58.3 GCA GAA GGA CTA A AJ_P985653613 E01 AJ_817 /5AmMC6/CCC AAC GTC AAC TAC 106534951 8699 59.8ACA GAA GGT CTA A AJ_P9 85653614 E02 AJ_818 /5AmMC6/CCC AAG TCG ACA ACA106534952 8730 60 GCA TTA GGT CTA A AJ_P9 85653615 E03 AJ_819/5AmMC6/CCC AAT TGG TCA GAA 106534953 8687 59.9 CTT TCC TTG CAA A AJ_P985653616 E04 AJ_820 /5AmMC6/CCC AAC CTA GGT CAA 106534954 8752 60.5GTT TAG GTT GCA A AJ_P9 85653617 E05 AJ_821 /5AmMC6/CCC AAG TCA TCT GCA106534955 8666 61.6 TCC ACA CTA GGA A AJ_P9 85653618 E06 AJ_822/5AmMC6/CCC AAA TCG CTT GAA 106534956 8690 61 CCA TAC CAT GGA A AJ_P985653619 E07 AJ_823 /5AmMC6/CCC AAA TCT GAA CTG 106534957 8763 58.8AGG AAC AAG CTA A AJ_P9 85653620 E08 AJ_824 /5AmMC6/CCC AAC GTG AGC ATC106534958 8770 61.2 AGG AAC ATT TGA A AJ_P9 85653621 E09 AJ_825/5AmMC6/CCC AAT CCC TAG TTC 106534959 8697 61.2 CAG TCA TGA GGA A AJ_P985653622 E10 AJ_826 /5AmMC6/CCC AAC TCC TAG TCC 106534960 8657 60.7TGT AGT CCA GAA A AJ_P9 85653623 E11 AJ_827 /5AmMC6/CCC AAG AGT CAA CTC106534961 8699 60.2 CAT GAA AGC CTA A AJ_P9 85653624 E12 AJ_828/5AmMC6/CCC AAG GTA GTC TCA 106534962 8755 61 GAG AAC ACC TGA A AJ_P985653625 F01 AJ_829 /5AmMC6/CCC AAG CTG TAG GAC 106534963 8779 59.8ATA AGA ACC GTA A AJ_P9 85653626 F02 AJ_830 /5AmMC6/CCC AAG TCC AAC TGA106534964 8739 60.4 AAC AGA GCT GTA A AJ_P9 85653627 F03 AJ_831/5AmMC6/CCC AAG TGC AAC TAC 106534965 8795 62.1 AGG ACA GTG TGA A AJ_P985653628 F04 AJ_832 /5AmMC6/CCC AAT GAA ACA GAC 106534966 8763 59.3AAG TAG CGT TCA A AJ_P9 85653629 F05 AJ_833 /5AmMC6/CCC AAA AAC TGT AGC106534967 8696 59.5 TTT CCC TTG GAA A AJ_P9 85653630 F06 AJ_834/5AmMC6/CCC AAT CCG TAG AGC 106534968 8761 60 AGT GAG TTT ACA A AJ_P985653631 F07 AJ_835 /5AmMC6/CCC AAG GTT CAT GCA 106534969 8672 60.6TCC TCT TCA AGA A AJ_P9 85653632 F08 AJ_836 /5AmMC6/CCC AAA CCT TTG TGG106534970 8761 61.3 AGT CAA GCA TGA A AJ_P9 85653633 F09 AJ_837/5AmMC6/CCC AAA CCT TTG TGA 106534971 8736 59.7 GCA GAG CAT TTA A AJ_P985653634 F10 AJ_838 /5AmMC6/CCC AAA CTG TTT CCC TTA 106534972 8672 60.5GAG CAG TCA A AJ_P9 85653635 F11 AJ_839 /5AmMC6/CCC AAG CTG TAG GAG106534973 8752 59.4 TTA CAT CTC TGA A AJ_P9 85653636 F12 AJ_840/5AmMC6/CCC AAG TGG ACA CTC 106534974 8706 61.3 CAG AAC TCT GTA A AJ_P985653637 G01 AJ_841 /5AmMC6/CCC AAC GTC ATC TGA 106534975 8699 59.8CAG AAC AGA CTA A AJ_P9 85653638 G02 AJ_842 /5AmMC6/CCC AAG TCC AAC GAA106534976 8699 60.8 GCA TGA CAC TTA A AJ_P9 85653639 G03 AJ_843/5AmMC6/CCC AAA GCC TAA AGC 106534977 8721 61.2 CTT TGG GTT ACA A AJ_P985653640 G04 AJ_844 /5AmMC6/CCC AAC CGT TCA AAC 106534978 8699 60.4GAC TAA GAG TCA A AJ_P9 85653641 G05 AJ_845 /5AmMC6/CCC AAT CGG AAC ACC106534979 8672 61.5 TTT GGT TTC CAA A AJ_P9 85653642 G06 AJ_846/5AmMC6/CCC AAT GAC CAT CAT 106534980 8687 60 GTT TGG CTT CAA A AJ_P985653643 G07 AJ_847 /5AmMC6/CCC AAG ACC ATG AGC 106534981 8672 60.5TCT CTT GTT CAA A AJ_P9 85653644 G08 AJ_848 /5AmMC6/CCC AAC TAG GTG AAG106534982 8755 61.9 TGA CAG CAT CCA A AJ_P9 85653645 G09 AJ_849/5AmMC6/CCC AAC AAG TTA GGA 106534983 8779 60.4 GAC TGA CTG CAA A AJ_P985653646 G10 AJ_850 /5AmMC6/CCC AAT CAG CAC ACG 106534984 8714 58.6AGT TCT AGT AAA A AJ_P9 85653647 G11 AJ_851 /5AmMC6/CCC AAA CGT CAC CTA106534985 8737 62.1 GGT TGG GTT ACA A AJ_P9 85653648 G12 AJ_852/5AmMC6/CCC AAA CCT TGT CTC TTA 106534986 8672 60.6 GCC ATG GAA A AJ_P985653649 H01 AJ_853 /5AmMC6/CCC AAA CCT TGT TAC 106534987 8712 60.6TGT GCT AGA GCA A AJ_P9 85653650 H02 AJ_854 /5AmMC6/CCC AAA CAG AGT GCT106534988 8681 60.8 TCC AAC TTC TGA A AJ_P9 85653651 H03 AJ_855/5AmMC6/CCC AAT CGT TCA CGA 106534989 8761 60.2 AGT AGG GTT ACA A AJ_P985653652 H04 AJ_856 /5AmMC6/CCC AAA AAC ATG TTC 106534990 8705 60.1CGT AGT TGC CAA A AJ_P9 85653653 H05 AJ_857 /5AmMC6/CCC AAT GAC CAC AAC106534991 8699 60.9 ATA GCA TGT CGA A AJ_P9 85653654 H06 AJ_858/5AmMC6/CCC AAG CAT AAA CAC 106534992 8739 60.2 TCT GGA CAG GTA A AJ_P985653655 H07 AJ_859 /5AmMC6/CCC AAG CTA ACA ACC 106534993 8699 59.7ATC GAG AGT CTA A AJ_P9 85653656 H08 AJ_860 /5AmMC6/CCC AAG TGA AAC TCA106534994 8699 59.7 CAC GAG ACT CTA A AJ_P9 85653657 H09 AJ_861/5AmMC6/CCC AAG TAA CAA ACC 106534995 8739 60.9 CAT GAG CTG TGA A AJ_P985653658 H10 AJ_862 /5AmMC6/CCC AAG TCG ACA TCA 106534996 8755 61.9CAG TCA AGG TGA A AJ_P9 85653659 H11 AJ_863 /5AmMC6/CCC AAG AAC TCT CTC106534997 8672 60.4 TGC ACA TTG TGA A AJ_P9 85653660 H12 AJ_864/5AmMC6/CCC AAC TGC ACA CAT 106534998 8687 60.1 GGT TTC TTT GAA A AJ_P1085653662 A01 AJ_865 /5AmMC6/CCC AAT AAA GCA CTT 106534999 8754 58.7TGA GAG TAC CGA A AJ_P10 85653663 A02 AJ_866 /5AmMC6/CCC AAA TCG CTT GTT106535000 8687 59.1 TAA CCT ACT GGA A AJ_P10 85653664 A03 AJ_867/5AmMC6/CCC AAC GTT GAG TTT 106535001 8745 59 AAG CTA CCA GAA A AJ_P1085653665 A04 AJ_868 /5AmMC6/CCC AAG TTT CAC TAC 106535002 8681 60ACG ACT TCG AGA A AJ_P10 85653666 A05 AJ_869 /5AmMC6/CCC AAT GGA GAC AGT106535003 8712 60.4 CTT CCC TTT GAA A AJ_P10 85653667 A06 AJ_870/5AmMC6/CCC AAG TTT CAC TGC 106535004 8712 61.1 ACT TCA AGG TGA A AJ_P1085653668 A07 AJ_871 /5AmMC6/CCC AAC CAG TCT GGT 106535005 8657 61.2TCT ACT ACA CGA A AJ_P10 85653669 A08 AJ_872/5AmMC6/CCC AAA TTC TCG TTC TCA 106535006 8712 59.9 GAG TCA GGA A AJ_P1085653670 A09 AJ_873 /5AmMC6/CCC AAG TTA CCA ACA 106535007 8699 60.1CCT GAG AAG CTA A AJ_P10 85653671 A10 AJ_874 /5AmMC6/CCC AAA CTA CTG TCA106535008 8779 60.1 AAG GAG TAG GCA A AJ_P10 85653672 A11 AJ_875/5AmMC6/CCC AAG TTC CCA AGA 106535009 8675 62 CCT ACA AGC TGA A AJ_P1085653673 A12 AJ_876 /5AmMC6/CCC AAT TTA GCC TAA 106535010 8714 59CAG CAA CAG GTA A AJ_P10 85653674 B01 AJ_877/5AmMC6/CCC AAA TCT GTT CTC TGC 106535011 8687 59 AAA GTC GTA A AJ_P1085653675 B02 AJ_878 /5AmMC6/CCC AAA GTC CTT GTC 106535012 8681 60.3TCA AAC TCA GGA A AJ_P10 85653676 B03 AJ_879 /5AmMC6/CCC AAA TCT TGT GTG106535013 8736 59.3 TCG AAG CAA CTA A AJ_P10 85653677 B04 AJ_880/5AmMC6/CCC AAG TGC AAC TGG 106535014 8770 60.4 AGA CAG ACT TTA A AJ_P1085653678 B05 AJ_881 /5AmMC6/CCC AAA CTG TCT TGT 106535015 8696 59.3TCG AAC AGC ATA A AJ_P10 85653679 B06 AJ_882 /5AmMC6/CCC AAT TTG TAC ATC106535016 8687 59.4 GCT TCA TCG GAA A AJ_P10 85653680 B07 AJ_883/5AmMC6/CCC AAT ACA GAA GGA 106535017 8739 58.9 GTA CCT GAC CTA A AJ_P1085653681 B08 AJ_884 /5AmMC6/CCC AAT CGC AAA GAA 106535018 8714 59.4GTA CCA GTT TCA A AJ_P10 85653682 B09 AJ_885 /5AmMC6/CCC AAC TGG TAG ACA106535019 8779 60.4 TGC ATA GAA GCA A AJ_P10 85653683 B10 AJ_886/5AmMC6/CCC AAG AGA ACT ACC 106535020 8795 62.2 GTT GTG AAG GCA A AJ_P1085653684 B11 AJ_887 /5AmMC6/CCC AAT TTC GAG AGT 106535021 8714 58.8CAC ATC AAC AGA A AJ_P10 85653685 B12 AJ_888 /5AmMC6/CCC AAC GGT AAG GCT106535022 8712 60.1 ACC TCT TTG TAA A AJ_P10 85653686 C01 AJ_889/5AmMC6/CCC AAC TAC GCT ACT 106535023 8723 58.5 AAA GTA AAG GCA A AJ_P1085653687 C02 AJ_890 /5AmMC6/CCC AAC GTG AGT TCG 106535024 8721 60TTA ACT ACC AGA A AJ_P10 85653688 C03 AJ_891 /5AmMC6/CCC AAT GGT CTA GCA106535025 8681 60.2 TTC AAC TAC CGA A AJ_P10 85653689 C04 AJ_892/5AmMC6/CCC AAT GTT TCA GAC 106535026 8672 60 CTG ACT ACC TGA A AJ_P1085653690 C05 AJ_893 /5AmMC6/CCC AAT AAC AGA ACC 106577190 8699 60.3CAT GCT CAG GTA A AJ_P10 85653691 C06 AJ_894 /5AmMC6/CCC AAA CAC GTT GCA106535028 8687 60 CTT TAC TTT GGA A AJ_P10 85653692 C07 AJ_895/5AmMC6/CCC AAT GCT GAC GTA 106535029 8723 59.3 CAC AAA CAA GTA A AJ_P1085653693 C08 AJ_896 /5AmMC6/CCC AAA GCT GTT GCT 106535030 8736 59.9GTT AAA CCG TAA A AJ_P10 85653694 C09 AJ_897 /5AmMC6/CCC AAC ATG TTG TGG106535031 8761 60.8 TAG CTA CCG AAA A AJ_P10 85653695 C10 AJ_898/5AmMC6/CCC AAA TCT CTG TGG 106535032 8761 60.2 TAG CAT AAC GGA A AJ_P1085653696 C11 AJ_899 /5AmMC6/CCC AAG AGC TCT CGT 106535033 8736 57.8GTT ACT AAA GTA A AJ_P10 85653697 C12 AJ_900 /5AmMC6/CCC AAA GCC TTG GTT106535034 8727 59.5 GTC AGT CTT AAA A AJ_P10 85653698 D01 AJ_901/5AmMC6/CCC AAG TAC CTC TAC 106535035 8657 60.2 TCT GAC TCA GGA A AJ_P1085653699 D02 AJ_902 /5AmMC6/CCC AAG GCA TAC AAC 106535036 8666 61.9TCT GAC CTG TCA A AJ_P10 85653700 D03 AJ_903 /5AmMC6/CCC AAC CAG TAA ACC106535037 8675 62.6 AGT GAC TTG CCA A AJ_P10 85653701 D04 AJ_904/5AmMC6/CCC AAG ACT CCT TGG 106535038 8721 60.6 TTC AAC GGT AAA A AJ_P1085653702 D05 AJ_905 /5AmMC6/CCC AAC TTA GGT AGG 106535039 8770 59.7TAG CAC ACT GAA A AJ_P10 85653703 D06 AJ_906 /5AmMC6/CCC AAA GTC CAG AGC106535040 8714 58.8 ACA TTT CAT AGA A AJ_P10 85653704 D07 AJ_907/5AmMC6/CCC AAG GCT ACA TGT 106535041 8675 61.6 CAC CTA ACC AGA A AJ_P1085653705 D08 AJ_908 /5AmMC6/CCC AAT GTC CAT GAC 106535042 8672 60.4TTT CCT AAC GGA A AJ_P10 85653706 D09 AJ_909 /5AmMC6/CCC AAG CAC ATG GTT106535043 8699 61.2 CCA CAT AAA CGA A AJ_P10 85653707 D10 AJ_910/5AmMC6/CCC AAG CCA TGT TGC 106535044 8699 61.4 ACA CTA CAA AGA A AJ_P1085653708 D11 AJ_911 /5AmMC6/CCC AAA CGC ATC CAA 106535045 8739 60.9AGT TAG GGT ACA A AJ_P10 85653709 D12 AJ_912 /5AmMC6/CCC AAC CAC TCG TAG106535046 8706 60.1 TCT ACT AGG AGA A AJ_P10 85653710 E01 AJ_913/5AmMC6/CCC AAA CTG TGT TGT 106535047 8752 59.8 CTC ACT AGA GGA A AJ_P1085653711 E02 AJ_914 /5AmMC6/CCC AAG TAC TCC TAC 106535048 8657 61.1TCG TAC ATG GCA A AJ_P10 85653712 E03 AJ_915 /5AmMC6/CCC AAT AAC ACG AAA106535049 8714 59.9 GCT TGT GCA TCA A AJ_P10 85653713 E04 AJ_916/5AmMC6/CCC AAT TTC TAG AAC 106535050 8687 59.6 TGT GCT TGC ACA A AJ_P1085653714 E05 AJ_917 /5AmMC6/CCC AAG GTG TAC CTT 106535051 8777 61.7TGA CCA GTG AGA A AJ_P10 85653715 E06 AJ_918 /5AmMC6/CCC AAG TTA CCT CTT106535052 8681 60.1 GCC ATA CGA GAA A AJ_P10 85653716 E07 AJ_919/5AmMC6/CCC AAG AAC GTT CTG 106535053 8714 59.6 CTC ATA GCA AAA A AJ_P1085653717 E08 AJ_920 /5AmMC6/CCC AAA CGC TTC TTC ATT 106535054 8696 59.4GTA ACA GGA A AJ_P10 85653718 E09 AJ_921 /5AmMC6/CCC AAG AGT CTC GAC106535055 8657 59.8 TCC TCT ACT AGA A AJ_P10 85653719 E10 AJ_922/5AmMC6/CCC AAG AGT ACA GAA 106535056 8690 59.8 CCT CAC TTT CGA A AJ_P1085653720 E11 AJ_923 /5AmMC6/CCC AAG TAC TGC TGA 106535057 8699 60.3CAC AAC TAA CGA A AJ_P10 85653721 E12 AJ_924 /5AmMC6/CCC AAA GCC TTT GGT106535058 8761 60.1 AGT CAG ACA GTA A AJ_P10 85653722 F01 AJ_925/5AmMC6/CCC AAA GGC TAC TCA 106535059 8714 59 GAA CAA CTT TGA A AJ_P1085653723 F02 AJ_926 /5AmMC6/CCC AAG TAC CTC ACT 106535060 8675 61.6CAA GCA TCA GGA A AJ_P10 85653724 F03 AJ_927 /5AmMC6/CCC AAA TAG TCT CAG106535061 8752 60.3 TGT GCT AGT GCA A AJ_P10 85653725 F04 AJ_928/5AmMC6/CCC AAG TCC ACT TTC 106535062 8697 62 TGC ACT AAG GGA A AJ_P1085653726 F05 AJ_929 /5AmMC6/CCC AAC AGT GCT TGC 106535063 8723 60.3AAA CAT CAA AGA A AJ_P10 85653727 F06 AJ_930/5AmMC6/CCC AAA CTT GTC TCT CTG 106535064 8712 59.5 AGT ACA GGA A AJ_P1085653728 F07 AJ_931 /5AmMC6/CCC AAA GTT CTC CAC 106535065 8730 60.2AAG TGT CAG AGA A AJ_P10 85653729 F08 AJ_932 /5AmMC6/CCC AAG TCT TCA CAC106535066 8690 60.4 TCA GAA CGT GAA A AJ_P10 85653730 F09 AJ_933/5AmMC6/CCC AAT CCG AAG TTG 106535067 8754 59 CGT AGA CTA AAA A AJ_P1085653731 F10 AJ_934 /5AmMC6/CCC AAG AAA CAT CGT 106535068 8699 60.1ACA CAG TCT CGA A AJ_P10 85653732 F11 AJ_935 /5AmMC6/CCC AAG AAC CAT CAC106535069 8675 62.4 CTG TCA GCA TGA A AJ_P10 85653733 F12 AJ_936/5AmMC6/CCC AAC GAC ATA CCT 106535070 8739 60.5 AAA GCA TGG TGA A AJ_P1085653734 G01 AJ_937 /5AmMC6/CCC AAG GTC ACA GCA 106535071 8666 61.9CTT TCC ACT AGA A AJ_P10 85653735 G02 AJ_938 /5AmMC6/CCC AAC GAG TTA CAC106535072 8705 59.6 GTT TGC CTA AAA A AJ_P10 85653736 G03 AJ_939/5AmMC6/CCC AAG TAC GCT AGT 106535073 8681 58.9 CTC TCA CAT AGA A AJ_P1085653737 G04 AJ_940 /5AmMC6/CCC AAA GTG TCT GAC 106535074 8681 59.9CAT ACT TAC CGA A AJ_P10 85653738 G05 AJ_941 /5AmMC6/CCC AAC GTT CCA TAC106535075 8699 60 CAA GGA CAT AGA A AJ_P10 85653739 G06 AJ_942/5AmMC6/CCC AAG GAC TTC GAC 106535076 8681 59.1 TTC CTA CTA AGA A AJ_P1085653740 G07 AJ_943 /5AmMC6/CCC AAT GAC GTT GTA 106535077 8681 60.5AAC CTC TCA CGA A AJ_P10 85653741 G08 AJ_944 /5AmMC6/CCC AAG CAC TGT GTA106535078 8690 61 AAC AAC CTT CGA A AJ_P10 85653742 G09 AJ_945/5AmMC6/CCC AAC ATG TAG AGA 106535079 8763 58.1 AAC TCT CGA GAA A AJ_P1085653743 G10 AJ_946 /5AmMC6/CCC AAC AGC TTC CTC 106535080 8672 59.5ATA GTC TTA GGA A AJ_P10 85653744 G11 AJ_947 /5AmMC6/CCC AAG TCC TAC ACA106535081 8675 61.3 CAG TCA TAC GGA A AJ_P10 85653745 G12 AJ_948/5AmMC6/CCC AAG TCC ATA CAT 106535082 8666 62.3 CCG AAC TGT GCA A AJ_P1085653746 H01 AJ_949 /5AmMC6/CCC AAG AAC TTC CAC 106535083 8681 61TTA GCA TGT GCA A AJ_P10 85653747 H02 AJ_950 /5AmMC6/CCC AAG GTT CTA CAT106535084 8690 60.7 CAC GTA CGC AAA A AJ_P10 85653748 H03 AJ_951/5AmMC6/CCC AAG AGT GCT ACC 106535085 8730 60 TTC GTA CAG AAA A AJ_P1085653749 H04 AJ_952 /5AmMC6/CCC AAA TAA GTC CTG 106535086 8763 58.8AAG GAA CGC ATA A AJ_P10 85653750 H05 AJ_953 /5AmMC6/CCC AAG TGC AAC GAG106535087 8739 61.4 ACC TTT GAC AAA A AJ_P10 85653751 H06 AJ_954/5AmMC6/CCC AAG CAC TGT TGA 106535088 8681 61.5 AAC CCT TTC GAA A AJ_P1085653752 H07 AJ_955 /5AmMC6/CCC AAA CTC GTC ACC 106535089 8681 61TTT GGG TAA ACA A AJ_P10 85653753 H08 AJ_956 /5AmMC6/CCC AAA GCC TTC TTG106535090 8721 60.2 GTC ATA GAC AGA A AJ_P10 85653754 H09 AJ_957/5AmMC6/CCC AAC AAC GGT ACT 106535091 8752 61.1 TTG TTG GTA GCA A AJ_P1085653755 H10 AJ_958 /5AmMC6/CCC AAC ATT CTG GTG 106535092 8752 60.6TTA CGA ACT GGA A AJ_P10 85653756 H11 AJ_959 /5AmMC6/CCC AAT GAA ACC ATC106535093 8699 61 CAT GTC AGA GCA A AJ_P10 85653757 H12 AJ_960/5AmMC6/CCC AAA ACT GAC CAT 106535094 8761 61.9 TGT GGT GTG CAA A

Example 11 Titration or Dilution Series

The ability to perform multiple experiments in parallel enablesstraightforward exploration of the counting results from samples with arange of starting concentrations or amounts of target, sometimes knownas a titration experiment or a dilution series.

An example of dilution series data for a labeled RPLPO gene sequence isshown in FIG. 26. Plotted in the figure is the counting result N foreach array where the nominal starting concentration of mRNA in thereaction is shown on the X axis.

Some of the graphical output from the analysis software for the sameexperiment is shown in FIG. 27. For each array, there is a compounddisplay with the following elements: (i) an intensity histogram (green)for the index spots, (ii) a blue line registered with the histogram,showing the dynamic threshold for spot counting, (iii) a 32×32 gridwhich is a digital representation of each array. A white site in thegrid denotes a spot whose intensity was above the dynamic threshold, anda black site denotes that the intensity was below the dynamic threshold,and (iv) the result N and the quality score Q is reported for each arrayas text.

While preferred embodiments of the present invention have been shown anddescribed herein, it will be obvious to those skilled in the art thatsuch embodiments may be provided by way of example only. Numerousvariations, changes, and substitutions will now occur to those skilledin the art without departing from the invention. It should be understoodthat various alternatives to the embodiments of the invention describedherein may be employed in practicing the invention.

What is claimed is:
 1. An array reader system comprising an output unitfor calculating an absolute number of target molecules in a sample,wherein the array reader system is configured to read an arraycomprising a plurality of labeled and non-labeled features.
 2. The arrayreader system of claim 1, further comprising an optical imaging system.3. The array reader system of claim 2, wherein the calculation is basedon transforming optical image data produced by the optical imagingsystem into a count of the number of labeled and non-labeled features.4. The array reader system of claim 1, wherein the output unit comprisesa digital processor and executable software.
 5. The array reader ofclaim 4, wherein the executable software comprises computer code fortransforming optical image data into a count of the number of labeledand non-labeled features.
 6. The array reader system of claim 1, whereinthe array comprises a microarray, microscope slide, or microwell plate.7. The array reader system of claim 2, wherein the optical imagingsystem has a magnification of less than 1, equal to 1, or greaterthan
 1. 8. The array reader system of claim 2, wherein the opticalimaging system comprises a fluorescence imaging system.
 9. The arrayreader system of claim 2, wherein the optical imaging system comprises aphosphorescence imaging system.
 10. The array reader system of claim 2,wherein the optical imaging system comprises an imaging system thatoperates in a transmitted light, reflected light, or scattered lightimaging mode, or combinations thereof.
 11. The array reader system ofclaim 8, 9, or 10, wherein the optical imaging system comprises one ormore image sensors.
 12. The array reader system of claim 11, wherein theone or more image sensors have a resolution of at least 320×240 pixels.13. The array reader system of claim 11, wherein the one or more imagesensors are CCD image sensors.
 14. The array reader system of claim 11,wherein the one or more image sensors are CMOS image sensors.
 15. Thearray reader system of claim 11, wherein the one or more image sensorscomprise one or more circuit boards.
 16. The array reader system ofclaim 8, 9, or 10, wherein the optical imaging system further comprisesone or more components selected from the group including, but notlimited to, a microscope objective, a camera lens, a finite-conjugatelens, an infinite-conjugate lens, a plano-convex lens, a double convexlens, a plano-concave lens, a double concave lens, an achromaticcemented doublet, or a bandpass filter.
 17. The array reader system ofclaim 8, wherein the fluorescence imaging system is designed for usewith fluorescein, Cy3, Cy5, or phycoerythrin fluorophores.
 18. The arrayreader system of claim 2, wherein the optical imaging system furthercomprises an illumination system including at least one light source.19. The array reader system of claim 18, wherein the at least one lightsource is an LED or LED assembly.
 20. The array reader system of claim18, wherein the at least one light source is electronically synchronizedwith the image sensor, the at least one light source being turned onwhen the image sensor is acquiring an image and turned off when theimage sensor is not acquiring an image.
 21. The array reader system ofclaim 18, wherein the illumination system is an off-axis illuminationsystem.
 22. The array reader system of claim 21, wherein the off-axisillumination system satisfies the Scheimpflug condition.
 23. The arrayreader system of claim 21, wherein the off-axis illumination system doesnot satisfy the Scheimpflug condition.
 24. The array reader system ofclaim 21, wherein the off-axis illumination subsystem is a Kohlerillumination system.
 25. The array reader system of claim 21, whereinthe off-axis illumination system is an Abbe illumination system.
 26. Thearray reader system of claim 18, wherein the illumination system is anepi-illumination system.
 27. The array reader system of claim 26,wherein the epi-illumination system is a Kohler illumination system. 28.The array reader system of claim 26, wherein the epi-illumination systemis an Abbe illumination system.
 29. The array reader system of claim 18,wherein the illumination system is a trans-illumination system.
 30. Thearray reader system of claim 29, wherein the trans-illumination systemis a Kohler illumination system.
 31. The array reader system of claim29, wherein the trans-illumination system is an Abbe illuminationsystem.
 32. The array reader system of claim 2, wherein the opticalimaging system further comprises a translation stage.
 33. The arrayreader system of claim 32, wherein the translation stage is asingle-axis translation stage.
 34. The array reader system of claim 32,wherein the translation stage is a dual-axis translation stage.
 35. Thearray reader system of claim 32, wherein the translation stage is amulti-axis translation stage.
 36. The array reader system of claim 4,wherein the executable software automatically locates features of thearray within the acquired image.
 37. The array reader system of claim36, wherein the executable software also performs local backgroundcorrection by (i) centering a predefined analysis window on each arrayfeature within an image, (ii) calculating an intensity value statisticfor signal and background pixels according to a predefined pattern ofpixels within the feature, and (iii) utilizing the signal and backgroundintensity value statistics to calculate a background corrected signalintensity value for each feature.
 38. The array reader system of claim37, wherein the executable software also performs a k-means clusteringanalysis of the background corrected signal intensity values for thecomplete set of array features, thereby determining a dynamic signalintensity threshold for discrimination between labeled and non-labeledfeatures of the array.
 39. The array reader system of claim 37, whereinthe executable software also performs a k-medoids clustering analysis ofthe background corrected signal intensity values for the complete set ofarray features, thereby determining a dynamic signal intensity thresholdfor discrimination between labeled and non-labeled features of thearray.
 40. The array reader system of claim 37, wherein the executablesoftware also performs a mixture model statistical analysis of thebackground corrected signal intensity values for the complete set ofarray features, thereby determining a dynamic signal intensity thresholdfor discrimination between labeled and non-labeled features of thearray.
 41. The array reader system of claim 37, wherein the executablesoftware also performs an empirical analysis based on sorting ofbackground corrected signal intensity values for the complete set ofarray features, thereby determining a dynamic signal intensity thresholdfor discrimination between labeled and non-labeled features of thearray.
 42. The array reader system of claim 37, wherein the executablesoftware also performs an empirical analysis based on sorting ofpairwise differences in background corrected signal intensity values forthe complete set of array features, thereby determining a dynamic signalintensity threshold for discrimination between labeled and non-labeledfeatures of the array.
 43. The array reader system of claim 37, whereinthe executable software also performs one or more statistical analysesof the background corrected signal intensity values for the complete setof array features, thereby determining a dynamic signal intensitythreshold for discrimination between labeled and non-labeled features ofthe array, and wherein the one or more statistical analyses are selectedfrom the list including, but not limited to, k-means clustering,k-medoids clustering, mixture model statistical analysis, or anempirical analysis.
 44. The array reader system of claim 5, 38, 39, 40,41, 42, or 43, wherein the executable software also calculates theabsolute number of target molecules in a sample based on the number oflabeled and non-labeled features detected and the predictions of thePoisson distribution.
 45. The array reader system of claim 44, whereinthe executable software also calculates a confidence interval for thenumber of target molecules.
 46. The array reader system of claim 2,wherein the optical imaging system and output unit are combined within asingle, stand-alone instrument.
 47. The array reader system of claim 2,wherein the optical imaging system and output unit are configured asseparate instrument modules.
 48. The array reader system of claim 3 or5, wherein the absolute number of target molecules in a sample iscalculated from the number of labeled and non-labeled features detectedand the predictions of the Poisson distribution.
 49. The array readersystem of claim 37, wherein the executable software also performs ananalysis of local background corrected signal intensities for thecomplete set of array features to determine a dynamic signal intensitythreshold, and wherein the analysis comprises fitting a model functionto the intensity data by varying model parameters.
 50. The array readersystem of claim 37, wherein the executable software also performs ananalysis of local background corrected signal intensities for thecomplete set of array features to determine a dynamic signal intensitythreshold, and wherein the analysis comprises maximizing a qualitymetric relating to a statistical difference between feature intensitiesabove the threshold and feature intensities below the threshold.